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AU2017348161B2 - System and method for identifying a location and/or an orientation of an electromagnetic sensor based on a map - Google Patents

System and method for identifying a location and/or an orientation of an electromagnetic sensor based on a map Download PDF

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Publication number
AU2017348161B2
AU2017348161B2 AU2017348161A AU2017348161A AU2017348161B2 AU 2017348161 B2 AU2017348161 B2 AU 2017348161B2 AU 2017348161 A AU2017348161 A AU 2017348161A AU 2017348161 A AU2017348161 A AU 2017348161A AU 2017348161 B2 AU2017348161 B2 AU 2017348161B2
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Prior art keywords
gridpoints
gridpoint
field strength
calculated
map
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AU2017348161A1 (en
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Lev A. Koyrakh
Sean M. Morgan
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Covidien LP
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Covidien LP
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Priority claimed from US15/337,129 external-priority patent/US10751126B2/en
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    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/20Surgical navigation systems; Devices for tracking or guiding surgical instruments, e.g. for frameless stereotaxis
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/06Devices, other than using radiation, for detecting or locating foreign bodies ; Determining position of diagnostic devices within or on the body of the patient
    • A61B5/061Determining position of a probe within the body employing means separate from the probe, e.g. sensing internal probe position employing impedance electrodes on the surface of the body
    • A61B5/062Determining position of a probe within the body employing means separate from the probe, e.g. sensing internal probe position employing impedance electrodes on the surface of the body using magnetic field
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/10Computer-aided planning, simulation or modelling of surgical operations
    • A61B2034/101Computer-aided simulation of surgical operations
    • A61B2034/102Modelling of surgical devices, implants or prosthesis
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/20Surgical navigation systems; Devices for tracking or guiding surgical instruments, e.g. for frameless stereotaxis
    • A61B2034/2046Tracking techniques
    • A61B2034/2051Electromagnetic tracking systems

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  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Surgery (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Animal Behavior & Ethology (AREA)
  • Veterinary Medicine (AREA)
  • Biomedical Technology (AREA)
  • Public Health (AREA)
  • Medical Informatics (AREA)
  • Molecular Biology (AREA)
  • General Health & Medical Sciences (AREA)
  • Physics & Mathematics (AREA)
  • Human Computer Interaction (AREA)
  • Biophysics (AREA)
  • Pathology (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Robotics (AREA)
  • Position Fixing By Use Of Radio Waves (AREA)

Abstract

Systems and methods for identifying a location and/or an orientation of an electromagnetic (EM) sensor navigated within an EM volume are provided. Calculated EM field strengths at each gridpoint of a second set of gridpoints of the EM volume are retrieved from a memory. An EM field is generated by way of an antenna assembly. A measured EM field strength is received from the EM sensor. A first gridpoint among a first set of gridpoints of the EM volume is identified based on the measured EM field strength and a high density (HD) map. The location and/or the orientation of the EM sensor is identified based on the HD map, using the first gridpoint as an initial condition, with the second set of gridpoints also including the first set of gridpoints.

Description

SYSTEM AND METHOD FOR IDENTIFYING A LOCATION AND/OR AN ORIENTATION OF AN ELECTROMAGNETIC SENSOR BASED ON A MAP BACKGROUND
Technical Field
100011 The present disclosure generally relates to electromagnetic navigation, and
more particularly to systems and methods for generating a map for electromagnetic
navigation and identifying a location and/or an orientation of a sensor based on the map.
Discussion of Related Art
10002] Electromagnetic navigation (EMN) has helped expand medical imaging,
diagnosis, prognosis, and treatment capabilities by enabling a location and/or an
orientation of a medical device and/or of a target of interest to be accurately determined
within a patient's body. Generally, an antenna generates an electromagnetic (EM) field in
an EM volume, a sensor incorporated onto a medical device senses an EM signal or
strength based on the field, and the EMN system identifies a sensor location based on the
sensed EM strength. The EM strength at each location in the EM volume is previously
measured or mapped to enable the sensor location to be identified in the EM volume by
comparing the sensed EM strength and the previously measured EM strength.
100031 In some cases, it may be desirable for the sensor to be a small-sized sensor,
such as a single-coil sensor, because, for instance, a small sized sensor may be navigable
to additional locations (e.g., narrower portions of a luminal network) within the patient, to
which a larger-sized sensor may not be navigable. Additionally, in contrast to large-size
sensors which sometimes must be removed from the patient during a procedure to make
room in a working channel for other tools, the small-sized sensor may remain within the
patient throughout the procedure without interfering with the other tools, thereby
facilitating EMN functionality throughout the procedure.
I
[00041 To enable a small-sized sensor such as a single-coil sensor to be accurately
located within an EM volume, it may be necessary to generate multiple (for instance, 6 or more)
geometrically diverse EM fields within the EM volume. However, because each of the EM
fields would require generation of a measured mapping of the corresponding EM strength at
each location in the EM volume, increasing the number of EM fields would increase the number
of mappings, which can be time consuming and laborious. Additionally, to improve the
accuracy with which the sensor location can be determined, precise measurements at many (for
example, thousands) of gridpoints within the EM volume may be needed, which could make the
generating of the mapping even more time consuming. Also, because of the potential variability
during the manufacturing processes and tolerances of electrical equipment, the mapping process
may need to be completed for each new antenna that is produced and for each electromagnetic
navigation system installation.
[0005] Given the foregoing, a need exists for improved systems and methods for
generating a map for electromagnetic navigation and identifying a location and/or an orientation
of a sensor based on the map.
SUMMARY
[0005a] It is an object of the present invention to substantially overcome or at least
ameliorate one or more of the above disadvantages.
[0005b] According to an aspect of the present invention, there is provided a method for
generating a high density (HD) map for identifying at least one of a location or an orientation of
an electromagnetic (EM) sensor within an EM volume in which an EM field is generated by
way of an antenna assembly, the method comprising: receiving a measured EM field strength at
each gridpoint of a first plurality of gridpoints of the EM volume from a measurement device;
calculating an EM field strength at each gridpoint of a second plurality of gridpoints of the EM
volume based on a geometric configuration of an antenna of the antenna assembly, wherein the
2a
number of the first plurality of gridpoints is fewer than the number of the second plurality of
gridppoints; and generating the HD map based on the measured EM field strength at each
gridpoint of the first plurality of gridpoints and the calculated EM field strength at each
gridpoint of the second plurality of gridpoints.
[0005c] According to another aspect of the present invention, there is provided an
apparatus for generating a high density (HD) map for identifying at least one of a location or an
orientation of an electromagnetic (EM) sensor within an EM volume in which an EM field is
generated by way of an antenna assembly, the apparatus comprising: a processor; and a memory
storing processor-executable instructions that, when executed by the processor, cause the
processor to: receive a measured EM field strength at each gridpoint of a first plurality of
gridpoints of the EM volume from a measurement device; calculate an EM field strength at each
gridpoint of a second plurality of gridpoints of the EM volume based on a geometric
configuration of an antenna of the antenna assembly wherein the number of the first plurality of
gridpoints is fewer than the number of the second plurality of gridppoints; and generate the HD
map based on the measured EM field strength at each gridpoint of the first plurality of
gridpoints and the calculated EM field strength at each gridpoint of the second plurality of
gridpoints.
[0006] The present disclosure is related to systems and methods for generating a map of
EM field strength, for example, a high density (HD) map, for electromagnetic navigation and
identifying a sensor location and/or orientation based on the map. In one example, the HD map
has a greater (e.g., finer) gridpoint resolution (that is, more gridpoints) in the EM volume than
that of a low density (LD) grid in the EM volume according to which EM field strength
measurements are taken and stored in a LD map. The HD map, in some aspects, is generated
based on the previously generated LD map of measured EM field strength and also based on EM
field strength calculations based, for instance on geometric configurations of antennas in an antenna assembly. In this manner, the location and/or the orientation of the sensor navigated within the patient's body can be accurately identified without the need to take EM field strength measurements at each of the many gridpoints of the HD map within the EM volume. This can enable the use of a small-sized sensor in EMN procedures while minimizing any increased burden of map generation.
100071 In accordance with one aspect of the present disclosure, a method is
provided for generating a high density (HD) map for identifying a location and/or an
orientation of an electromagnetic (EM) sensor within an EM volume in which an EM
field is generated by way of an antenna assembly. The method includes receiving a
measured EM field strength at each gridpoint of a first set of gridpoints of the EM volume
from a measurement device. An EM field strength at each gridpoint of a second set of
gridpoints of the EM volume is calculated based on a geometric configuration of an
antenna of the antenna assembly. The IID map is generated based on the measured EM
field strength at each gridpoint of the first set of gridpoints and the calculated EM field
strength at each gridpoint of the second set of gridpoints.
10008] In another aspect of the present disclosure, the antenna assembly generates
at least six EM waveforms as components of the EM field.
100091 In a further aspect of the present disclosure, the EM field strength is
calculated along a three axes coordinate system for each of the at least six EM waveforms.
10010] In yet another aspect of the present disclosure, the EM field strength is
measured by way of a sensor having three coils corresponding to the three axes,
respectively.
100111 In still another aspect of the present disclosure, the second set of gridpoints
includes each gridpoint of the first set of gridpoints.
[00121 In another aspect of the present disclosure, the generating the HD map
includes calculating an error between the measured EM field strength and the calculated
EM field strength, at each gridpoint of the first set of gridpoints. An error for each
gridpoint of the second set of gridpoints is interpolated based on the calculated error at
each gridpoint of the first set of gridpoints. The interpolated error and the calculated EM
field strength at each gridpoint of the second set of gridpoints are added to generate the
HD map
[00131 In a further aspect of the present disclosure, the error is calculated based
on a difference between the measured EM field strength and the calculated EM field
strength at each gridpoint of the first set of gridpoints.
[0014] In yet another aspect of the present disclosure, the error is based on at least
one of an L1 or L2 norm of differences between the measured EM field strength and the
calculated EM field strength along the three axes.
[0015] In still another aspect of the present disclosure, the method further includes
calculating a pseudo-inverse of the calculated EM field strength at each gridpoint of the
second set of gridpoints.
[0016] In another aspect of the present disclosure, the HD map further includes
the pseudo-inverse of the calculated EM field strength at each gridpoint of the second
plurality of gridpoints.
[0017] In accordance with another aspect of the present disclosure an apparatus is
provided for generating an HD map for identifying a location and/or an orientation of an
EM sensor within an EM volume in which an EM field is generated by way of an antenna
assembly. The apparatus includes a processor and a memory storing processor-executable
instructions that, when executed by the processor, cause the processor to receive, from a
measurement device, a measured EM field strength at each gridpoint of a first set of gridpoints of the EM volume. An EM field strength at each gridpoint of a second set of gridpoints of the EM volume is calculated based on a geometric configuration of at least one antenna of the antenna assembly. The -D map is generated based on the measured
EM field strength at each gridpoint of the first set of gridpoints and the calculated EM
field strength at each gridpoint of the second set of gridpoints.
10018] In another aspect of the present disclosure, the antenna assembly generates
at least six EM waveforms as components of the EM field.
100191 In still another aspect of the present disclosure, the EM field strength is
calculated along a three axes coordinate system for each of the at least six EM waveforms.
10020] In a further aspect of the present disclosure, the EM field strength is
measured with a sensor having three coils corresponding to the three axes, respectively.
100211 In yet another aspect of the present disclosure, the second set of gridpoints
includes each gridpoint of the first set of gridpoints.
10022] In another aspect of the present disclosure, the generating of the HD map
includes calculating an error between the measured EM field strength and the calculated
EM field strength, at each gridpoint of the first set of gridpoints. An error for each
gridpoint of the second plurality of gridpoints is interpolated based on the calculated error
at each gridpoint of the first plurality of gridpoint. The interpolated error and the
calculated EM field strength at each gridpoint of the second plurality of gridpoints are
added to generate the HD map.
10023] In yet another aspect of the present disclosure, the error is calculated based
on a difference between the measured EM field strength and the calculated EM field
strength at each gridpoint of the first set of gridpoints.
[00241 In a further aspect of the present disclosure, the error is based on an Li
and/or L2 norm of differences between the measured EM field strength and the calculated
EM field strength along the three axes.
100251 In still another aspect of the present disclosure, the memory further stores
instructions that, when executed by the processor, cause the processor to calculate a
pseudo-inverse of the calculated EM field strength at each gridpoint of the second set of
gridpoints.
[00261 In another aspect of the present disclosure, the HD map further includes
the pseudo-inverse of the calculated EM field strength at each gridpoint of the second set
of gridpoints.
[0027] In accordance with another aspect of the present disclosure, a method is
provided for identifying a location and/or an orientation of an EM sensor navigated
within an EM volume. The method includes retrieving, from a memory, a calculated EM
field strength at each gridpoint of a second set of gridpoints of the EM volume. An EM
field is generated by way of an antenna assembly. A measured EM field strength is
received from the EM sensor. A first gridpoint among a first set of gridpoints of the EM
volume is identified based on the measured EM field strength and a HD map. The
location and/or the orientation of the EM sensor are identified based on the HD map,
using the first gridpoint as an initial condition. The second set of gridpoints includes the
first plurality of gridpoints.
[00281 In another aspect of the present disclosure, the antenna assembly includes
at least six antennas, each of the antennas including multiple loops.
100291 In yet another aspect of the present disclosure, the multiple loops have a
geometric configuration.
100301 In a further aspect of the present disclosure, the HD map includes a
calculated EM field strength for each gridpoint of the second set of gridpoints in the EM
volume.
100311 In still another aspect of the present disclosure, the calculated EM field
strength is based on the respective geometric configurations of the at least six antennas.
10032] In another aspect of the present disclosure, the HD map further includes a
pseudo-inverse of the calculated EM field strength at each gridpoint of the second
plurality of gridpoints.
100331 In yet another aspect of the present disclosure, the identifying the first
gridpoint includes identifying an orientation vector n , where(a,b,c) is a gridpoint in
the first set of gridpoints, satisfying the following condition: i B V, where
B -'is a pseudo-inverse ofB , which is a calculated EM field strength at gridpoint
(a,b,c) in the ID map. A difference between St,,cy ii,,c> and V is calculating. A
gridpoint (A,B,C), from among the first set of gridpoints, where a difference between
BBABC) -n and V is the smallest, is selected, as the first gridpoint.
100341 In a further aspect of the present disclosure, the identifying the location
and/or the orientation includes identifying an orientation vector id, where (d,e,f) is a
gridpoint in the second set of gridpoints and is located nearby (e.g. within a
predetermined distance) from the first gridpoint (A,B,C), satisfying the following
condition:fiiV whereBSde is a pseudo-inverse of B which isa
calculated EM field strength at gridpoint (d,e,f) in the HD map. A difference between
B nWf5 and V is calculated- A second gridpoint (D,EF) from among the second set
of gridpoints, where a difference between BD,EF) (,F) hesmallest,isselected.
100351 In still another aspect of the present disclosure, in is related to the
orientation of the EM sensor.
[00361 In another aspect of the present disclosure, the second gridpoint (D,E,F) is
the location of the EM sensor.
[00371 In accordance with another aspect of the present disclosure, a system is
provided for identifying a location and/or an orientation of an EM sensor navigated
within an EM volume. The system includes an antenna assembly, the EM sensor, a
processor, and a memory. The antenna assembly is configured to radiate an EM field
within the EM volume. The EM sensor is configured to measure an EM field strength
based on the radiated EM field. The memory stores a calculated EM field strength at each
gridpoint of a second set of gridpoints of the EM volume. The memory also stores
processor-executable instructions that, when executed by the processor, cause the
processor to retrieve, from the memory, the calculated EM field strength at each gridpoint
of the second set of gridpoints. A first gridpoint among a first set of gridpoints of the EM
volume is identified based on the measured EM field strength and the -D map. The
location and/or the orientation of the EM sensor are identified based on the HD map,
using the first gridpoint as an initial condition. The second set of gridpoints includes the
first set of gridpoints.
[00381 In a further aspect of the present disclosure, the antenna assembly includes
at least six antennas, each of the antennas including a plurality of loops.
[00391 In still another aspect of the present disclosure, the plurality of loops has a
geometric configuration.
100401 In another aspect of the present disclosure, the -I map includes a
calculated EM field strength at each gridpoint of the second set of gridpoints in the EM
volume.
100411 In yet another aspect of the present disclosure, the calculated EM field
strength is based on the respective geometric configurations of the at least six antennas.
100421 In another aspect of the present disclosure, the HD map further includes a
pseudo-inverse of the calculated EM field strength at each gridpoint of the second set of
gridpoints.
10043] In another aspect of the present disclosure, the identifying the first
gridpoint includes identifying an orientation vector ncg , where (a,bc) is a gridpoint in
the first set of gridpoints, satisfying the following condition:it 35 -V, where
13 'is a pseudo-inverse of B , which is a calculated EM field strength at gridpoint
(a,b,c) in the HD map. A difference between B -n ag and V is calculated. A
gridpoint (A,BC) from among the first plurality of gridpoints, where a difference
between -n and V is the smallest, is selected as the first gridpoint.
100441 In yet another aspect of the present disclosure, the identifying the location
and/or the orientation includes identifying an orientation vector iidewhere (d,e,f) is a
gridpoint in the second set of gridpoints and is located nearby (e.g., within a
predetermined distance from) the first gridpoint (A,B,C), satisfying the following
condition: ii 6d, V, whereB5 4 isa pseudo-inverse of B which is a
calculated EM field strength at gridpoint (d,e,f) in the H) map. A difference between
B -i and V is calculated. A second gridpoint (D,E,F) from among the second
plurality of gridpoints, where a difference betweenB(D,EF) i(D,FF) and V is the smallest is
selected.
100451 In another aspect of the present disclosure, f(D,F, F)is related to the
orientation of the EM sensor.
[00461 In a further aspect of the present disclosure, the second gridpoint (D,E,F)
is the location of the EM sensor.
[00471 Any of the aspects and embodiments of the present disclosure may be
combined without departing from the scope of the present disclosure.
BRIEF DESCRIPTION OF THE DRAWINGS
100481 Objects and features of the presently disclosed systems and methods will
become apparent to those of ordinary skill in the art when descriptions of various
embodiments are read with reference to the accompanying drawings, of which:
100491 FIG. I shows an example electromagnetic navigation (EMN) system, in
accordance with the present disclosure;
[0050] FIG. 2 is a block diagram of a portion of the EMN system of FIG. 1, in
accordance with the present disclosure;
[0051] FIG. 3 is a graphical illustration of example low density measurements and
related curves, in accordance with the present disclosure;
[00521 FIG. 4 is a flowchart illustrating an example method for generating a high
density map, in accordance with the present disclosure;
100531 FIG. 5 is a flowchart illustrating an example method for identifying a
location and/or an orientation of a sensor, in accordance with the present disclosure;
[0054] FIG. 6 is a graphical illustration of an example error function, having
multiple local minima, of a discrepancy between a measurement value and a calculated
value, in accordance with the present disclosure; and
[0055] FIG. 7 is a block diagram of a computing device for use in various
embodiments of the present disclosure.
DETAILED DESCRIPTION
100561 The present disclosure is related to systems and methods for generating a
high density (HD) map and identifying a location and/or an orientation of a sensor, which
may include at least one coil, based on theIID map. In some aspects, the respective
geometric configurations the antennas enable automated and highly repeatable processes
for reproducing such antennas and/or for mathematically calculating the expected or
theoretical EM strength at every[ID gridpoint within an EM volume (for instance, where
the antennas have geometric configurations based on linear portions of printed circuit
board (PCB) traces, which facilitate use of the superposition principle in computing the
total contribution of the fields generated by way of each antenna to the total combined
EM field within the volume). These mathematical calculations may be combined with
actual measurements made in a coarse coordinate system, which includes fewer
gridpoints than the number of gridpoints used for the mathematically calculated EM
strength. In this way, the time and/or cost related to making the measurements can be
lowered and a HD map can be generated and used in a repeatable, efficient, and cost
effective manner.
10057] Further, the present disclosure is related to systems and methods for
identifying a location and/or an orientation of an EM sensor by using the HD map. In
general, the EM sensor senses EM strengths, and an EMN system compares the sensed
EM strengths with the expected EM strengths of the HD map and identifies the location
and the orientation of the EM sensor.
100581 In an aspect of the present disclosure, a fine coordinate system (e.g., a ID
coordinate system or set of gridpoints) is used to describe a coordinate system of the EM
volume, which includes more gridpoints than those in a coarse coordinate system (e.g., a
LD coordinate system or set of gridpoints) of the EM volume. In some aspects, every gridpoint of the coarse coordinate system may be included in the fine coordinate system.
In general, the coarse coordinate system is utilized for actual EM field strength
measurements and the fine coordinate system is utilized for mathematical calculations of
EM field strength.
[00591 FIG. I illustrates an example electromagnetic navigation (EMN) system
100, which is configured to identify a location and/or an orientation of a medical device,
or sensor thereof, navigating (e.g., to a target) within the patient's body by using an
antenna assembly, which includes a plurality of antennas and generates EM fields. The
EMN system 100 is further configured to augment CT, MRI, or fluoroscopic images in
navigation through patient's body toward a target of interest, such as a deceased portion
in aluminal network of a patient's lung.
100601 The EMN system 100 includes a catheter guide assembly 110, a
bronchoscope 115, a computing device 120, a monitoring device 130, an EM board 140, a
tracking device 160, and reference sensors 170. The bronchoscope 115 is operatively
coupled to the computing device 120 and the monitoring device 130 via a wired
connection (as shown in FIG. 1) or wireless connection (not shown).
[00611 The bronchoscope 115 is inserted into the mouth of a patient 150 and
captures images of the luminal network of the lung. In the EMN system 100, inserted into
the bronchoscope 115 is a catheter guide assembly 110 for achieving access to the
periphery of the luminal network of the lung of the patient 150. The catheter guide
assembly 110 may include an extended working channel (EWC) 111 with an EM sensor
112 at the distal portion of the EWC 111. A locatable guide catheter (LG) may be inserted
into the EWC 111 with another EM sensor at the distal portion of the LG. The EM sensor
112 at the distal portion of the EWC 111 or the LG is used to identify a location and/or an
orientation of the EWC 1 IIor the LG while navigating through the luminal network of the lung. Due to the size restriction in the EWC 111 or the LG, in some embodiments, the
EM sensor 112 may include only one single coil for detecting EM strength of an EM field
over the patient 150. However, the number of coils in the EM sensor is not limited to one
but may be two or more.
100621 The computing device 120, such as, a laptop, desktop, tablet, or other
similar computing device, includes a display 122, one or more processors 124, memory
126, an AC current driver 127 for providing AC current signals to the antenna assembly
145, a network card 128, and an input device 129. The particular configuration of the
computing device 120 illustrated in FIG. I is provided as an example, but other
configurations of the components shown in FIG. 1 as being included in the computing
device 120 are also contemplated. In particular, in some embodiments, one or more of the
components (122, 124, 126, 127, 128, and/or 129) shown in FIG. I as being included in
the computing device 120 may instead be separate from the computing device 120 and
may be coupled to the computing device 120 and/or to any other component(s) of the
system 100by way of one or more respective wired or wireless path(s) to facilitate the
transmission of power and/or data signals throughout the system 100. For example,
although not shown in FIG. 1, the AC current driver 127 may, in some example aspects,
be separate from the computing device 120 and may be coupled to the antenna assembly
145 and/or coupled to one or more components of the computing device 120, such as the
processor 124 and the memory 126, by way of one or more corresponding paths.
100631 In some aspects, the EMN system 100 may also include multiple
computing devices, wherein the multiple computing devices are employed for planning,
treatment, visualization, or helping clinicians in a manner suitable for medical operations.
The display 122 may be touch-sensitive and/or voice-activated, enabling the display 122
to serve as both input and output devices. The display 122 may display two dimensional
(2D) images or three dimensional (3D) model of a lung to locate and identify a portion of
the lung that displays symptoms of lung diseases.
[00641 The one or more processors 124 execute computer-executable instructions.
The processors 124 may perform image-processing functions so that the 3D model of the
lung can be displayed on the display 122 or location algorithm to identify a location and
an orientation of the EM sensor 112. In embodiments, the computing device 120 may
further include a separate graphic accelerator (not shown) that performs only the image
processing functions so that the one or more processors 124 may be available for other
programs. The memory 126 stores data and programs. For example, data may be mapping
data for the EMN or any other related data such as a HD map, image data, patients'
medical records, prescriptions and/or history of the patient's diseases.
100651 The HD map may include a plurality of gridpoints in a fine coordinate
system of the EM volume in which a medical device (e.g., the EWC 111, LG, treatment
probe, or other surgical devices) is to be navigated, and expected EM strengths at each of
the plurality of gridpoints. When the EM sensor 112 senses EM strength at a point, the
one or more processors 124 may compare the sensed EM strength with the expected EM
strengths in the HD map and identify the location of the EM sensor 112 within the EM
volume. Further, an orientation of the medical device may be also calculated based on the
sensed EM strength and the expected EM strengths in theID map.
[00661 As shown in FIG. 1, the EM board 140 is configured to provide a flat
surface for the patient 150 to lie upon and includes an antenna assembly 145. When the
patient 150 lies upon on the EM board 140, the antenna assembly 145 generates an EM
field sufficient to surround a portion of the patient 150 or the EM volume. The antenna
assembly 145 includes a plurality of antennas, each of which may include a plurality of
loops. In one aspect, each antenna is configured to generate an EM waveform having a corresponding frequency. The number of antennas may be at least six. In an aspect, the number of antennas may be nine so that nine different EM waveforms can be generated.
100671 In another aspect, a time multiplexing method is employed in generating
the EM waveforms. For example, the antennas of the antenna assembly 145 may generate
EM waveforms with the same frequency at different times during a period. In another
aspect, frequency multiplexing method may be employed, where each antenna generates
EM waveform having a frequency differentfrom each other. In still another aspect,
combination of the time multiplexing and frequency multiplexing methods may be
employed. The antennas are grouped into more than one group. Antennas in the same
group generate EM waveforms having the same frequency but at different times.
Antennas in different groups may generate EM waveforms having different frequencies
from each other. Corresponding de-multiplexing method is to be used to separate EM
waveforms.
100681 In an aspect, each antenna may have a geometric configuration (for
instance, where the antennas each have geometric configurations based onlinear portions
of printed circuit board (PCB) traces or wires, which facilitate use of the superposition
principle in computing the total contribution of the fields generated by way of each
antenna to the total combined EM field within the volume) so that each portion of the
plurality of loops can be expressed as mathematical relationship or equations, as
described in further detail below. The magnetic field can thus be computed for each trace
on the antenna and the contributions from all traces can be summed. Based on this
geometric configuration, expected EM strength at each gridpoint in the HD map can be
theoretically or mathematically calculated. Additional aspects of such example antennas
and methods of manufacturing the antennas are disclosed in U.S. Patent Application No.
15/337,056 , entitled "Electromagnetic Navigation Antenna Assembly and
Electromagnetic Navigation System Including the Same," filed on October 28, 2016 and
having attorney docket number 356580.USUI (1988-252 A), the entire contents of which
are hereby incorporated by reference herein.
100691 FIG. 2 shows a block diagram of a portion of the example electromagnetic
navigation system 100 of FIG. 1, according to the present disclosure. In general, the
computing device 120 of the EMN system 100 controls the antenna assembly 145
embedded in the EM board 140 to generate anEM field, receives sensed results from the
EM sensor 112, and determines a location and an orientation of the EM sensor 112 in the
EM volume.
[00701 The computing device 120 includes a clock 205, which generates a clock
signal used for generating theEM field and sampling the sensed results. Since the same
clock signal is used for generating the EM field and sampling the sensed EM field,
synchronization between the magnetic field generation circuitry (e.g., a waveforn
generator 210) and the waveform acquisition circuitry (e.g., a digitizer 215) may be
achieved. In other words, when the clock 205 provides a clock signal to the waveform
generator 210 and the digitizer 215, the EM waveforms generated by the antenna
assembly 145 are digitally sampled by digitizer 215 substantially at the same time. The
digitizer 215 may include an analog-to-digital converter (ADC, which is not shown) to
digitally sample the sensed results and an amplifier (which isnot shown) to amplify the
magnitude of the sensed result so that the magnitude of the sensed results is within the
operable range of the ADC. In an aspect, the digitizer 215 may include a pre-amplifier
and post-amplifier so that the magnitude of the sensed result is amplified to be within the
operable range of the ADC by the pre-amplifier and digital samples are also amplified to
the magnitude of the sensed result by the post-amplifier.
100711 The demodulator 220 demodulates the digital samples to remove unwanted
signals (e.g., noises) and to restore the EM waveforms, which have been generated by the
antenna assembly 145. The demodulator 220 may use timed-multiplexing method,
frequency de-multiplexing method, or combination of both to separate and identify the
EM waveforms depending on the method used by the antennas of the antenna assembly
145 to generate the EM waveforms, and to determine EM strength affected by each of the
antenna of the antenna assembly 145.
100721 For example, when the antenna assembly 145 includes six antennas, the
demodulator 220 is capable of identifying six EM strengths, which is sensed by the EM
sensor 112, for the six antennas, respectively. In a case when the number of antennas is
nine, the outputs of the demodulator 220 may be expressed in a form of a nine by one
matrix. Based on the modulation method (e.g., time multiplexing, frequency multiplexing,
or a combination thereof) utilized by the antennas, the demodulator 220 demodulates the
sensed result.
100731 For example, when the antennas of the antenna assembly 145 utilize
frequency multiplexing, the demodulator 220 may use a set of finely tuned digital filters.
Orthogonal frequency division multiplexing may also be utilized, in which the EM field
and sampling frequencies are chosen in such a way that only the desired frequency from a
specific antenna is allowed to pass while other frequencies are precisely stopped. In an
aspect, the demodulator 220 may use a multiple tap orthogonal frequency matched filter,
in which the digital filter for a specific frequency is tuned to the desired demodulation
window.
100741 The memory 126 may store data and programs related to identification of a
location and an orientation. The data includes a high density (HD) map 225, which
includes a plurality of gridpoints according to the fine coordinate system for the EM volume and expected EM strengths at the gridpoints. The HD map 225 may be based on three-axis coordinate system, where each gridpoint has three coordinates corresponding to the three axes, respectively. In this case, the expected EM strength at each gridpoint may include one EM strength value along each axis for each EM waveform. For example, if there are nine antennas generating nine different EM waveforms, each of which having a separate frequency, and three axes are x, y, and z axes, the expected EM strength may include nine EM strength values along the x axis, nine EM strength values along the y axis, and nine EM strength values along the z axis, at each gridpoint. Such expected EM strength at each gridpoint may be expressed in a nine by three matrix form.
[00751 The HD map 225 may be made with computations 230, which includes
theoretically calculated EM strengths at each axis at each gridpoint in the fine coordinate
system, and measurement 235, which includes measurements at each axis at each
gridpoint in the coarse coordinate system. The fine coordinate system includes all the
gridpoints in the coarse coordinate system and the gridpoints of the fine coordinate
system are more finely distributed than those of the coarse coordinate system. By using
the geometric configuration of the antennas of the antenna assembly 145, measurement
may not have to be made with the fine coordinate system. Rather, the measurement may
be made in the coarse coordinate system and theoretical computations may be made in the
fine coordinate system. By combining the measurements 235 in the coarse coordinate
system with the theoretical computations 230 in the fine coordinate system, the HD map
225 may be generated. Generation of the HD map 225 based on the measurement 235 and
calculations 230 will be described in further detail with respect to FIG. 4 below.
100761 After passage of time or due to foreign objects near the EMN system 100,
measurements by the EM sensor 112 or other hardware may need to be calibrated. Such
calibration data may be also stored in the memory 126 in a form of sensor calibration 240 and hardware calibration 245.
10077] When the computing device 120 receives measurement data from the EM
sensor 112 via the demodulator 220, the computing device 120 uses the location
algorithm 250, which is also stored in the memory 126, with the:HID map 225 to identify
the location and the orientation of the EM sensor 112 inthe fine coordinate system.
Identification of the location and/or the orientation will be described in further detail with
respect to FIG. 5 below.
100781 The location algorithm 250 may utilize any error minimization algorithm
in identifying the location and the orientation of the EM sensor 112. For example,
Levenberg-Marquardt algorithm may be employed to minimize errors between the
expected EM strengths of the IHl density map and the sensed results. Other error
minimization methods or algorithms, which a person having ordinary skill in the art can
readily appreciate, may also be utilized without departing from the scope of this
disclosure.
100791 The memory 126 further includes applications 255, which can be utilized
by the computing device 120 of the EMN system 100 and which uses information
regarding the location and the orientation of the EM sensor 112. Such application 255
may be a displaying application, which displays a graphicalrepresentation of a medical
device, on which the EM sensor 112 is mounted or installed, at the location of the EM
sensor 112 and along the orientation of the EM sensor 112 in the EM volume, an
application for treatment, which determines whether a medical device is near a target of
interest, or any other applications, which use the location and the orientation of the EM
sensor 112.
100801 FIG. 3 is a graphical illustration of multiple curves 320, 325, 330, and 340,
as well as discrete EM field strength measurements 315a-315i taken in the coarse coordinate system. The horizontal axis may represent any axis among x, y, and z axes for the EM volume and the vertical axis represents a magnitude of EM field strengths.
Gridpoints of the coarse coordinate system are shown separated by 50 millimeters and
measured EM strengths at the gridpoints of the coarse coordinate system are shown as
black dots 315a-315i.
[0081] In some aspects, measurements may be taken at a specific hospital rooms
and beds, where the EIN system 100 will be used, byway of a measurement jig, which
includes three coils sensing an EM field strength in each of three different directions (e.g.,
x, y, and z axes). Examples of such a measurement jig are disclosed by Provisional U.S.
Patent Application No. 62/237,084, entitled "Systems And Methods For Automated
Mapping And Accuracy-Testing," filed on October 5, 2015, the entire contents of which
are hereby incorporated herein by reference.
[00821 Based on the measurement values at LD gridpoints 315a-315i,
interpolation may be used to generate first and second interpolated curves, 320 and 325.
In one example, the first interpolated curve 320 is generated by a linear interpolation
method and the second interpolated curve 325 is generated by B-spline interpolation.
Calculated EM strengths at gridpoints in the HD map are also interpolated to generate a
third interpolated curve 330.
[00831 As shown in box 335, the first, second, and third interpolated curves 320,
325, 330 are substantially different from each other between two gridpoints 315h and
315i. The first interpolated curve 320 is lower than the third interpolated curve 330, and
the second interpolated curve 325 is much higher than the second and third interpolated
curves 325 and 330. Due to these big differences, an error maybe apparent if only one of
the three interpolated curves is used.
100841 In order to minimize such differences, a fourth interpolated curve 340 is
used. The fourth curve 340 is generated by calculating discrepancies between theoretical
calculations and measurements at the LD gridpoints, such as 315a-315i, and interpolating
the discrepancies for the IDgridpoints. By adding the fourth interpolated curve 340 to
the third interpolated curve 330 at the HD gridpoints, expected EM strength at each
gridpoints in the HD map is obtained and higher accuracy may be obtained. Detailed
descriptions regarding how to generate the HD map is described with respect to FIG. 4
below.
100851 FIG. 4 is a flowchart illustrating an example method 400 for generating an
HD map based on theoretical calculations in the fine coordinate system and
measurements in the coarse coordinate system. Measurements maybe performed for the
EM field generated by the antennas of the antenna assembly 145 of FIG. 1, each of which
having a corresponding geometric configuration. At 410, EM field measurements at all
gridpoints in the coarse coordinate system are received from ameasurement jig. The
measurements may include three different measurements along three axes in the coarse
coordinate system for each EM waveform. Thus, when there are nine antennas, the
measurements at one gridpoint may include three values for the three different axes and
nine of three values for the nine different waveforns, respectively. In an aspect, these
measurements maybe in a form of nineby three matrix.
100861 At 420, based on the geometric configuration of each antenna of the
antenna assembly 145, EM field strength is theoretically or mathematically calculated. As
described above, each antenna includes a plurality of loops, which have geometric
configurations. In other words, each loop of the antenna can be expressed in a form of
mathematical equations or is made of simply linear portions. Thus, EM strength at any
gridpoints in the fine coordinate system may be calculated by using Biot-Savart-Laplace law as follows: por Idl xr' B~r)= 3(1), where B(r) is the EM strength at the gridpoint r influenced by the linear portion C, po is a magnetic constant of the vacuum permeability, 4ax10-7 V-s/(A-m), is a symbol of line integral on the linear portion C, I is the magnitude of the current passing through the linear portion C, dl is a vector whose magnitude is the length of the differential element of the linear portion C in the direction of current, r' is a displacement vector from the differential element dl of the linear portion C to the gridpoint r, and x is a vector symbol representing a cross product between two vectors. Since the linear portion C is a simple line and each loop of the antenna includes multiple linear portions, total EM strength at the gridpoint r can be a sum of the EM strengths influenced by all the linear portions of the antenna. Further, the EM strength at the gridpoint r by the plural antennas is calculated in the same way. In other words, the total EM strength at gridpoint r may include three calculated values for the three different axes (e.g., x, y, and z axes) for one antenna, and nine of three calculated values for the nine antennas, in a case when there are nine antennas. In an aspect, the calculated EM strength maybe expressed in a nine by three matrix form.
[00871 At 430, a discrepancy is calculated between the measured EM field and the
calculated EM field at each gridpoint in the coarse coordinate system. In an aspect, the
discrepancy may be made smaller by calibrating parameters of the three coil sensor of the
measurement jig, calibrating the antennas, or calibrating parameters (e.g., frequencies or
phases for the waveform generator 210) of the computing device of the EMN system.
100881 At 440, the calculated discrepancies at gridpoints in the coarse coordinate
system are interpolated for gridpoints in the fine coordinate system. Any method of interpolation including linear interpolation, b-spline interpolation, etc. may be used.
10089] At 450, the interpolated discrepancies are added to the theoretical
calculations of the EM field to from expected EM field strength at each gridpoint in the
fine coordinate system. The expected EM field strength at each gridpoint may be in a
form of a nine by three matrix in a case when there are nine separate EM waveforms. The
HD map may further include a pseudo-inverse of the expected EM field strength at each
gridpoint in the HD map. This pseudo-inverse may be used in identifying a location and
an orientation of the EM sensor, which is described in further detail with respect to FIG. 5
below.
10090] FIG. 5 is a flowchart illustrating an example method 500 for identifying a
location and/or an orientation of an EM sensor, for example, mounted on a medical
device, which is navigated within a patient's body, in accordance with the present
disclosure. The method 500 may be used while a medical device navigates inside the
patient's body. At 510, the HD map, which includes expected EM field strength at each
gridpoint of the I-ID map, is retrieved from a memory. As described above, the expected
EM field strengths are based on the theoretical computations in the fine coordinate system
and measurements in the coarse coordinate system.
10091] The EM sensor mounted on the medical device periodically transmits
sensed EM field strength to an EMN computing device, which digitally samples the
sensed EM field strength. The EMN computing device measures the EM field strength
based on the digital samples in step 520.
100921 At 530, it is determined whether an initial location is set as an initial
condition. If it is determined that the initial location is not set, the EMN computing device
compares all gridpoints in the coarse coordinate system with the measured EM field
strength, simply pickups, to find an approximate gridpoint in the coarse coordinate system near the location of the EM sensor, as an initial location, at 540.
[00931 In an embodiment, a following error function may be used at 540:
E =Y(B(a,b,c) n(a,b,c) -V +b n - g2 (2),
where E is the error value, a is a counter, N is the number of antennas, (a,bc) is a
gridpoint in the coarse coordinate system, B,(ab,c) is a vector, one by three matrix,
including an expected EM field strength at (a,b,c) influenced by the a-th antenna, "-" is a
symbol of dot product between two vectors, n(ab,c) is an orientation of the EM sensor,
and V, is a vector, one by one matrix, including a pickup influenced by thea-th antenna,
b is a parameter to control a gain weight, and g is a gain of the EM sensor. In an aspect,
the parameter b is used when the gain of the EM sensor is known and fixed. The value for
the parameter b may be chosen so as not to dominate the error function E. In another
aspect, when the gain of the EM sensor is not known, the parameter b may be set to zero
or the gain squared, g2 , is assumed to be equal tothe squared norm of the orientation
vector n.
[00941 In some examples, for convenience, the parameter b is assumed to be zero.
In this case, the error function Ebecomes:
Ib (a,bc)n- 2(a,b,c)- Nj (3).
This error function is useful in identifying a location in the coarse or fine coordinate
system. In an aspect, the error function is not limited to the above equation (2) or (3) and
can be any error function that a person of ordinary skill in the art would readily appreciate without departing from the scope of this disclosure. For example, the error function E may be:
B(a,b,c) -V orB(a,b,c) -V
where |11 or 12 represents an L1 or L2 norm of the vector inside of the symbol,
respectively.
100951 Referring briefly to FIG. 6, a curve of an error function along one axis is
shown to illustrate how selection of an initial location may impact the determination of a
location that provides the global minimum of the error. The horizontal axis represents a
location along one axis (e.g., x, y, or z axis) and the vertical axis represents a magnitude
of the error function. If the initial location is set to be near X0 or X 1, the location giving a
local minimum will be between X 0 and X. If the initial location is set to be X5 or X6 , the
location giving a local minimum will be between X 5 and X6 . In contrast, if the initial
location is set to be one of X2 , X 3 , or X4, the location giving a local minimum will be
between X3 and X 4 , which gives the accurate global minimum. Thus, referring back to
FIG. 5, in a case when there is no set initial location, themethod 500 evaluates the error
function at every gridpoint in the coarse coordinate system to find afirst gridpoint, which
provides the global minimum, in step 540.
100961 The error function E includes a term, the orientation vector n, which, at
540, may also be identified as follows:
n(a,b,c)= B(ab,c)- 1-V (4),
where (a,b,c)Y is a pseudo-inverse of (a,b,c) , and V includes pickups. In one
example, if the total number of antennas in the antenna assembly is nine, B(a,b,c) is a
nine by three matrix, 1(a,b,c) 1 is a three by nine matrix, and V is a nine by one matrix.
Thus, B(a,b,c)'- V results in a three by one matrix, which is a column vector
representing an orientation matrix, n(a, b, c) at gridpoint (a,b,c) in the coarse coordinate
system.
100971 Based on equation (3). the error function is evaluated. Errors of all
gridpoints in the coarse coordinate system are compared with each other, and the
gridpoint that provides the smallest error is selected as a first gridpoint and is set as the
initial location at 540. After the initial location is set at 540, 550 follows. Also, at 530,
when it is determined that the initial location is set, the step 550 is performed.
100981 At 550, a predetermined number of gridpoints around the initial location
are selected to calculate the error function in the same way as in equation (2) or (3). For
example, if the predetermined number of gridpoints is three, three gridpoints from the
initial location in both directions along x, y, and z axes form a cube, 7 by 7 by 7
gridpoints. Thus, 343 gridpoints are selected to calculate the error function, and one
among the selected gridpoints, which provides the smallest error, is selected as a second
gridpoint, i.e., the location of the EM sensor. The corresponding orientation vector is also
set as the orientation of the EM sensor in step 550. The second gridpoint is set as the
initial location in step 560.
[00991 According to one aspect, in step 540, the error may be compared with a
predetermined threshold. If the error is less than the predetermined threshold, that
gridpoint is selected as the second gridpoint or the location of the EM sensor and
corresponding orientation vector is selected as the orientation of the EM sensor.
[001001 In step 570, it is determined whether the target has been reached. When it
is determined that the target has not been reached, steps 520-570 are repeated until the
target is reached. Otherwise, the method 500 ends.
1001011 Turning now to FIG. 7, there is shown a block diagram of a computing
device 700, which can be used as the computing device 120 of the EMN system 100, the
tracking device 160, or a computer performing the method 400 of FIG. 4 or the method
500 of FIG. 5. The computing device 700 may include a memory 702, a processor 704, a
display 706, network interface 708, an input device 710, and/or output module 712.
1001021 The memory 702 includes any non-transitory computer-readable storage
media for storing data and/or software that is executable by the processor 704 and which
controls the operation of the computing device 700. In an embodiment, the memory 702
may include one or more solid-state storage devices such as flash memory chips.
Alternatively or in addition to the one or more solid-state storage devices, the memory
702 may include one or more mass storage devices connected to the processor 704
through a mass storage controller (not shown) and a communications bus (not shown).
Although the description of computer-readable media contained herein refers to a solid
state storage, it should be appreciated by those skilled in the art that computer-readable
storage media can be any available media that can be accessed by the processor 704. That
is, computer readable storage media include non-transitory, volatile and non-volatile,
removable and non-removable media implemented in any method or technology for
storage of information such as computer-readable instructions, data structures, program
modules or other data. For example, computer-readable storage media include RAM,
ROM, EPROM, EEPROM, flash memory or other solid state memory technology, CD
ROM, DVD, Blu-Ray or other optical storage, magnetic cassettes, magnetic tape,
magnetic disk storage or other magnetic storage devices, or any other medium which can
be used to store the desired information and which can be accessed by the computing
device 700.
[001031 The memory 702 may store application 716 and data 714. The application
716 may, when executed by the processor 704, cause the display 706 to present user
interface 718 on its screen.
1001041 The processor 704 may be a general purpose processor, a specialized
graphic processing unit (GPU) configured to perform specific graphics processing tasks
while freeing up the general purpose processor to perform other tasks, and/or any number
or combination of such processors.
[001051 The display 706 may be touch-sensitive and/or voice-activated, enabling
the display 706 to serve as both an input and output device. Alternatively, a keyboard (not
shown), mouse (not shown), or other data input devices may be employed.
[001061 The network interface 708 may be configured to connect to a network such
as a local area network (LAN) consisting of a wired network and/or a wireless network, a
wide area network (WAN), a wireless mobile network, a Bluetooth network, and/or the
internet. For example, the computing device 700 may receive measurement data and
variables, and perform the method 400 of FIG. 4 to generate aHD map. The computing
device 700 may receive updates to its software, for example, application 716, via network
interface 708. The computing device 700 may also display notifications on the display
706 that a software update is available.
[001071 In another aspect, the computing device 700 may receive computed
tomographic (CT) image data of a patient from a server, for example, a hospital server,
internet server, or other similar servers, for use during surgical ablation planning. Patient
CT image data may also be provided to the computing device 700 via a removable
memory.
1001081 Input device 710 may be any device by means of which a user may interact
with the computing device 700, such as, for example, a mouse, keyboard, foot pedal,
touch screen, and/or voice interface.
1001091 Output module 712 may include any connectivity port or bus, such as, for
example, parallel ports, serial ports, universal serial busses (USB), or any other similar
connectivity port known to those skilled in the art.
100110] The application 716 may be one or more software programs stored in the
memory 702 and executed by the processor 704 of the computing device 700. During
generation of the HD map, one or more software programs in the application 716 may be
loaded from the memory 702 and executed by the processor 704 to generate the H1D map.
In an embodiment, during a navigation phase, one or more programs in the application
716 may be loaded, identify the location and the orientation of an EM sensor mounted on
a medical device, and display the medical device at the location along the orientation on a
screen overlaid with other imaging data, such as CT data or a three dimensional model of
a patient. In another embodiment, during a treatment phase, one or more programs in the
application 716 may guide a clinician through a series of steps to identify a target, size the
target, size a treatment zone, and/or determine an access route to the target for later use
during the procedure phase. In some other embodiments, one or more programs in the
application 716 may be loaded on computing devices in an operating room or other
facility where surgical procedures are performed, and is used as a plan or map to guide a
clinician performing a surgical procedure by using the information regarding the location
and the orientation.
1001111 The application 716 may be installed directly on the computing device 700,
or may be installed on another computer, for example a central server, and opened on the
computing device 700 via the network interface 708. The application 716 may run natively on the computing device 700, as a web-based application, or any other format known to those skilled in the art. In some embodiments, the application 716 will be a single software program having all of the features and functionality described in the present disclosure. In other embodiments, the application 716 may be two or more distinct software programs providing various parts of these features and functionality. For example, the application 716 may include one software program for generating a HD map, another one for identifying a location and an orientation, and a third program for navigation and treatment program. In such instances, the various software programs forming part of the application 716 may be enabled to communicate with each other and/or import and export various data including settings and parameters.
[001121 The application 716 may communicate with a user interface 718 which
generates a user interface for presenting visual interactive features to a user, for example,
on the display 706 and for receiving input, for example, via a user input device. For
example, user interface 718 may generate a graphical user interface (GUI) and output the
GUI to the display 706 for viewing by a user.
[001131 In a case that the computing device 700 may be used as the EMN system
100, the control workstation 102, or the tracking device 160, the computing device 700
may be linked to the display 130, thus enabling the computing device 700 to control the
output on the display 130 along with the output on the display 706. The computing device
700 may control the display 130 to display output which is the same as or similar to the
output displayed on the display 706. For example, the output on the display 706 may be
mirrored on the display 130. Alternatively, the computing device 700 may control the
display 130 to display different output from that displayed on the display 706. For
example, the display 130 may be controlled to displayguidance images and information
during the surgical procedure, while the display 706 is controlled to display other output, such as configuration or status information of an electrosurgical generator 101 as shown in FIG. 1.
1001141 The application 716 may include one software program for use during the
planning phase, and a second software program for use during the treatment phase. In
such instances, the various software programs forming part of application 716 may be
enabled to communicate with each other and/or import and export various settings and
parameters relating to the navigation and treatment and/or the patient to share information.
For example, a treatment plan and any of its components generated by one software
program during the planning phase may be stored and exported to be used by a second
software program during the procedure phase.
100115] Although embodiments have been described in detail with reference to the
accompanying drawings for the purpose of illustration and description, it is to be
understood that the inventive processes and apparatus are not to be construed as limited.
It will be apparent to those of ordinary skill in the art that various modifications to the
foregoing embodiments may be made without departing from the scope of the disclosure.
For example, various steps of the methods described herein may be implemented
concurrently and/or in an order different from the example order(s) described herein.

Claims (20)

CLAIMS:
1. A method for generating a high density (HD) map for identifying at least one of a location or an orientation of an electromagnetic (EM) sensor within an EM volume in which an EM field is generated by way of an antenna assembly, the method comprising: receiving a measured EM field strength at each gridpoint of a first plurality of gridpoints of the EM volume from a measurement device; calculating an EM field strength at each gridpoint of a second plurality of gridpoints of the EM volume based on a geometric configuration of an antenna of the antenna assembly, wherein the number of the first plurality of gridpoints is fewer than the number of the second plurality of gridppoints; and generating the HD map based on the measured EM field strength at each gridpoint of the first plurality of gridpoints and the calculated EM field strength at each gridpoint of the second plurality of gridpoints.
2. The method according to claim 1, wherein the antenna assembly generates at least six EM waveforms as components of the EM field.
3. The method according to claim 2, wherein the EM field strength is calculated along a three axes coordinate system for each of the at least six EM waveforms.
4. The method according to claim 3, wherein the EM field strength is measured by way of a sensor having three coils corresponding to the three axes, respectively.
5. The method according to claim 1, wherein the second plurality of gridpoints includes each gridpoint of the first plurality of gridpoints.
6. The method according to claim 5, wherein the generating the HD map includes: calculating an error between the measured EM field strength and the calculated EM field strength, at each gridpoint of the first plurality of gridpoints; interpolating an error for each gridpoint of the second plurality of gridpoints based on the calculated error at each gridpoint of the first plurality of gridpoints; and adding the interpolated error and the calculated EM field strength at each gridpoint of the second plurality of gridpoints to generate the HD map.
7. The method according to claim 6, wherein the error is calculated based on a difference between the measured EM field strength and the calculated EM field strength at each gridpoint of the first plurality of gridpoints.
8. The method according to claim 6, wherein the error is based on at least one of an Li or L2 norm of differences between the measured EM field strength and the calculated EM field strength along the three axes.
9. The method according to claim 1, further comprising calculating a pseudo-inverse of the calculated EM field strength at each gridpoint of the second plurality of gridpoints.
10. The method according to claim 9, wherein the HD map further includes the pseudo inverse of the calculated EM field strength at each gridpoint of the second plurality of gridpoints.
11. An apparatus for generating a high density (HD) map for identifying at least one of a location or an orientation of an electromagnetic (EM) sensor within an EM volume in which an EM field is generated by way of an antenna assembly, the apparatus comprising: a processor; and a memory storing processor-executable instructions that, when executed by the processor, cause the processor to: receive a measured EM field strength at each gridpoint of a first plurality of gridpoints of the EM volume from a measurement device; calculate an EM field strength at each gridpoint of a second plurality of gridpoints of the EM volume based on a geometric configuration of an antenna of the antenna assembly wherein the number of the first plurality of gridpoints is fewer than the number of the second plurality of gridppoints; and generate the HD map based on the measured EM field strength at each gridpoint of the first plurality of gridpoints and the calculated EM field strength at each gridpoint of the second plurality of gridpoints.
12. The apparatus according to claim 11, wherein the antenna assembly generates at least six EM waveforms as components of the EM field.
13. The apparatus according to claim 12, wherein the EM field strength is calculated along a three axes coordinate system for each of the at least six EM waveforms.
14. The apparatus according to claim 13, wherein the EM field strength is measured with a sensor having three coils corresponding to the three axes, respectively.
15. The apparatus according to claim 11, wherein the second plurality of gridpoints includes each gridpoint of the first plurality of gridpoints.
16. The apparatus according to claim 15, wherein generating the HD map includes: calculating an error between the measured EM field strength and the calculated EM field strength, at each gridpoint of the first plurality of gridpoints; interpolating an error for each gridpoint of the second plurality of gridpoints based on the calculated error at each gridpoint of the first plurality of gridpoint; and adding the interpolated error and the calculated EM field strength at each gridpoint of the second plurality of gridpoints to generate the HD map.
17. The apparatus according to claim 16, wherein the error is calculated based on a difference between the measured EM field strength and the calculated EM field strength at each gridpoint of the first plurality of gridpoints.
18. The apparatus according to claim 16, wherein the error is at least one of an Li or L2 norm of differences between the measured EM field strength and the calculated EM field strength along the three axes.
19. The apparatus according to claim 11, wherein the memory further stores instructions that, when executed by the processor, cause the processor to calculate a pseudo-inverse of the calculated EM field strength at each gridpoint of the second plurality of gridpoints.
20. The apparatus according to claim 19, wherein the HD map further includes the pseudo-inverse of the calculated EM field strength at each gridpoint of the second plurality of gridpoints.
Covidien LP Patent Attorneys for the Applicant/Nominated Person SPRUSON&FERGUSON
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US15/337,129 US10751126B2 (en) 2016-10-28 2016-10-28 System and method for generating a map for electromagnetic navigation
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