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WO2004077333A1 - Procede et appareil d'analyse de donnees images - Google Patents

Procede et appareil d'analyse de donnees images Download PDF

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Publication number
WO2004077333A1
WO2004077333A1 PCT/IB2004/050138 IB2004050138W WO2004077333A1 WO 2004077333 A1 WO2004077333 A1 WO 2004077333A1 IB 2004050138 W IB2004050138 W IB 2004050138W WO 2004077333 A1 WO2004077333 A1 WO 2004077333A1
Authority
WO
WIPO (PCT)
Prior art keywords
image data
datasets
nodule
data set
workstation
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/IB2004/050138
Other languages
English (en)
Inventor
Frans W. Zonneveld
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Koninklijke Philips NV
Original Assignee
Koninklijke Philips Electronics NV
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Koninklijke Philips Electronics NV filed Critical Koninklijke Philips Electronics NV
Publication of WO2004077333A1 publication Critical patent/WO2004077333A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/46—Arrangements for interfacing with the operator or the patient
    • A61B6/467—Arrangements for interfacing with the operator or the patient characterised by special input means
    • A61B6/469—Arrangements for interfacing with the operator or the patient characterised by special input means for selecting a region of interest [ROI]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/12—Arrangements for detecting or locating foreign bodies
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/06—Devices, other than using radiation, for detecting or locating foreign bodies ; Determining position of diagnostic devices within or on the body of the patient
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/08—Clinical applications
    • A61B8/0833—Clinical applications involving detecting or locating foreign bodies or organic structures
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30061—Lung

Definitions

  • the invention relates to a method and apparatus for analyzing image data.
  • a method for analyzing image data representing a person's body part comprising a first step of collecting a first image data set and a second step of collecting a second image data set, wherein both the first image data set and the second image data set represent the same body part, whereafter the First image data set and the second image data set are compared to identify differences with respect to a region of interest in said body part.
  • a problem with the prior art method and apparatus is that once an abnormality or a deviation is identified, the issue arises to determine whether the concerning abnormality or deviation, in particular the nodules that are found, are malignant or not.
  • the invention is intended to provide a method and apparatus, notably a medical workstation by which this determination of malignancy or non-malignancy can be carried out.
  • the method according to the invention is to this end characterized in that the region of interest is selected to include at least one nodule present in the first image data set, and that the comparison between the first image data set and the second image data set is carried out to identify a growth-behavior of the at least one nodule present in the first image data set.
  • the growth behavior is derived from examing differences between the first and second images.
  • the growth behavior represents the changes, for example in size, over time of the nodule at issue.
  • the change and hence the growth behavior may be postive, negative or neutral.
  • the workstation according to the invention receives the first and image datasets by way of an input module.
  • the image datasets represent the same part of an object to be examined, such as a patient to be examined.
  • the workstation is provided with a selection module to select a region of interest in which at least one nodule is shown, from the image datasets.
  • the workstation is further provided with a comparator which functions to compare the first and second image datasets and identify the growth behavior of the nodule at issue. It is possible that the nodule being examined has disappeared in the second image data set or has remained essentially the same in regard of its characterizing features as compared to the nodule in the first image data set. If in such case the time elapsed between the moment of collecting the first image data set and the moment of collecting the second image data set is large enough, for instance typically three to six months, the conclusion is warranted that the nodule under examination is non-malignant.
  • the nodule under examination has doubled in volume in the said timeframe of typically three to six months (the exact timeframe being dependent on the age of the person under examination), the conclusion is warranted that the nodule under examination is malignant.
  • the workstation of the invention is for example provided with a qualifier module which attributes the relevant qualification such as malignant or non-malignant to the nodule at issue. To support the ease of comparison the first image data set with the second image data set, it is desirable that prior to comparing these data sets, the data sets are matched to each other.
  • matching of the first and the second image data sets includes translating and/or rotating and/or deforming of either one of the first and the second image data sets.
  • translating and/or rotating of the image data sets may be required in order to correct for different positioning of the person on the examining table at the time the first image data set and the second image data set are collected. This may particularly be the case when much time has elapsed between the two moments that the image data sets are collected.
  • the deformation of the first image data set or second image data set may be desirable to take account for differences in breath hold situation; such differences account for possible differences in the location of the region of interest under examination.
  • the workstation of the invention is at option provided with a matching module to perform the matching of the image data sets to one another.
  • the function of matching includes translating and/or rotating and/or deforming of either one of the first and the second image data sets
  • a dividing of the data sets into sub- volumes is carried out, whereby the said sub- volumes of one image data set jointly represent the person's lungs.
  • a more accurate matching and subsequent comparison of the regions of interest under examination can be carried out.
  • the workstation of the invention is provided with a selection module.
  • Relatively high repeatability of the method according to the invention can be secured when the division into sub-volumes comprises the definition of separation-planes, at least one of which includes the carina of the person's lungs.
  • the carina identifies with the splitting point of the person's two main stem bronchi.
  • a second separation plane may be located in the middle of the person's diaphragm or midriff.
  • the invention is further embodied in an apparatus for analyzing image data representing a person's body party, comprising a processor for receiving and processing a first image data set and a second image data set representing said person's body part, said processor including a comparator for comparing the first and the second image data sets and an output organ for reporting a result from said comparison, and which is characterized in that the processor is adapted to operate the method according to the invention.
  • a processor for example the selection module, comparator, qualifier module, matching module are implemented in software, but they may be implemented in specially designed circuitry, such as in the form of integrated circuits.
  • the invention also relates to a computer program as defined in Claim 11. Loading the computer program of the invention in the working memory of a general workstation enable the workstation to perform the method of the invention.
  • the computer program of the invention can be made available on a data carrier such as a CD-ROM, or may be downloaded from a data network such as the world- wide web.
  • the invention is also embodied in a software carrier and in software which is designed to control the operation of a processor, so as to implement the method as discussed above.
  • Figure 1 shows a diagrammatic representation of a workstation in which the invention is employed.
  • the workstation 1 is provided with the input module 11 which receives the first and second datasets.
  • the verifying module assesses tha the images if the first and second data sets relate to the same body part. Meaningful comparison to assess the growth behavior of a nodule requires the images to concern the same body part.
  • the verifying mdoule assesses from the datasets the timesapn that elapsed between the acquisition of the images. Particularly meaningful results are acieved when the elapsed timespan is in the range of three to six months.
  • the first and second data sets are applied to the selection module 12 which selects 121 the sub- volumes form the first and second datasets.
  • the selection module is arranged to select sub-volumes that relate to the lung fields of the patient to be examined.
  • the selected sub- volumes of the first and second data sets are fed to the selection module to select 13 the region of interest on the basis of the occurrence of at least one nodule in the region of interest in the first and second datasets, or more precisely in the selected sub- volumes.
  • the respective regions of interest of both first and second datasets are mutually matched by the matching module 14.
  • the matching module 14 notably carries out geometric transformations, such as translation and rotation in order to remove differences that are irrelevant for comparing growth of nodules, but which are causes by differences in the imaging circumstances that applied when the first and second datasets are generated.
  • the matching module 14 derives matched versions of the first and second datasets and applies these to the qualifier module 16.
  • the qualifier module attributes a qualification, such as benign or malignant, to the at least one nodule in the first and second datasets. This qualification is further assigned to the first and/or second datasets by an assignment module 17 which supports a graphical representation of the attributed qualification and outputs the attributed dataset to a monitor 18. On the monitor 18 the attributed dataset is displayed which shows both the anatomy represented by the first or second datasets with the attributed qualification.

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  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Medical Informatics (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • General Health & Medical Sciences (AREA)
  • Physics & Mathematics (AREA)
  • Radiology & Medical Imaging (AREA)
  • Biomedical Technology (AREA)
  • Veterinary Medicine (AREA)
  • Pathology (AREA)
  • High Energy & Nuclear Physics (AREA)
  • Biophysics (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Molecular Biology (AREA)
  • Surgery (AREA)
  • Animal Behavior & Ethology (AREA)
  • Optics & Photonics (AREA)
  • Public Health (AREA)
  • Human Computer Interaction (AREA)
  • Quality & Reliability (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Apparatus For Radiation Diagnosis (AREA)

Abstract

Procédé d'analyse de données images représentant une partie du corps humain, comprenant une première étape consistant à recueillir une première série de données images et une deuxième étape consistant à recueillir une deuxième série de données images, ces deux séries de données représentant la même partie du corps, après quoi les deux séries sont comparées l'une à l'autre afin d'identifier des différences par rapport à une région à étudier dans ladite partie du corps. Cette région à étudier est choisie de façon à inclure au moins un nodule présent dans la première série de données images, et la comparaison entre les deux séries de données est effectuée afin d'identifier le comportement en croissance du ou des nodules présents dans la première série de données images.
PCT/IB2004/050138 2003-02-28 2004-02-23 Procede et appareil d'analyse de donnees images Ceased WO2004077333A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
EP03100500.2 2003-02-28
EP03100500 2003-02-28

Publications (1)

Publication Number Publication Date
WO2004077333A1 true WO2004077333A1 (fr) 2004-09-10

Family

ID=32921618

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/IB2004/050138 Ceased WO2004077333A1 (fr) 2003-02-28 2004-02-23 Procede et appareil d'analyse de donnees images

Country Status (1)

Country Link
WO (1) WO2004077333A1 (fr)

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1998036683A1 (fr) 1997-02-25 1998-08-27 Temple University - Of The Commonwealth System Of Higher Education Dispositif de filtration a disques rotatifs avec moyen permettant de reduire les forces axiales
US6236742B1 (en) * 1997-07-09 2001-05-22 Peter H. Handel Coherent superscan early cancer detection
US20030018245A1 (en) * 2001-07-17 2003-01-23 Accuimage Diagnostics Corp. Methods for generating a lung report

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1998036683A1 (fr) 1997-02-25 1998-08-27 Temple University - Of The Commonwealth System Of Higher Education Dispositif de filtration a disques rotatifs avec moyen permettant de reduire les forces axiales
US6236742B1 (en) * 1997-07-09 2001-05-22 Peter H. Handel Coherent superscan early cancer detection
US20030018245A1 (en) * 2001-07-17 2003-01-23 Accuimage Diagnostics Corp. Methods for generating a lung report

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
KANAZAWA K ET AL: "Computer-aided diagnosis for pulmonary nodules based on helical CT images", NUCLEAR SCIENCE SYMPOSIUM, 1997. IEEE ALBUQUERQUE, NM, USA 9-15 NOV. 1997, NEW YORK, NY, USA,IEEE, US, 9 November 1997 (1997-11-09), pages 1635 - 1639, XP010275739, ISBN: 0-7803-4258-5 *
KO J P ET AL: "Chest CT: automated nodule detection and assessment of change over time-preliminary experience", RADIOLOGY, OAK BROOK,IL, US, vol. 218, no. 1, January 2001 (2001-01-01), pages 267 - 273, XP002266047, ISSN: 0033-8419 *

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