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WO2009080792A1 - Procédé pour déterminer des propriétés ou pour déterminer et/ou repérer la position d'une partie caractéristique de l'oeil - Google Patents

Procédé pour déterminer des propriétés ou pour déterminer et/ou repérer la position d'une partie caractéristique de l'oeil Download PDF

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Publication number
WO2009080792A1
WO2009080792A1 PCT/EP2008/068107 EP2008068107W WO2009080792A1 WO 2009080792 A1 WO2009080792 A1 WO 2009080792A1 EP 2008068107 W EP2008068107 W EP 2008068107W WO 2009080792 A1 WO2009080792 A1 WO 2009080792A1
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WO
WIPO (PCT)
Prior art keywords
characteristic
eye
tracking
determining
image
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/EP2008/068107
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German (de)
English (en)
Inventor
Thomas Schuhrke
Günter Meckes
Keith Thornton
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.)
Carl Zeiss Surgical GmbH
Original Assignee
Carl Zeiss Surgical GmbH
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 Carl Zeiss Surgical GmbH filed Critical Carl Zeiss Surgical GmbH
Publication of WO2009080792A1 publication Critical patent/WO2009080792A1/fr
Priority to US12/801,689 priority Critical patent/US8662667B2/en
Anticipated expiration legal-status Critical
Priority to US14/147,046 priority patent/US9089283B2/en
Ceased legal-status Critical Current

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Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
    • A61B3/10—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions
    • A61B3/113—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions for determining or recording eye movement

Definitions

  • the invention relates to a method for determining properties or determining and / or tracking the position of a characteristic eye component according to the preamble of claim 1 and an apparatus for carrying out the method according to claim 12.
  • LASIK refractive errors of the human eye
  • Another example of this is a cataract surgery in which a natural lens of the human eye, which has become clouded, is replaced by an artificial lens.
  • the surgeon performs such an intervention under a surgical microscope. After a circular opening of the anterior capsule leaf, the lens is usually shattered and aspirated. Subsequently, an artificial lens is inserted into the empty capsular bag.
  • a surgical microscope for eye surgery which superimposes a pattern on the eye to be operated on.
  • the pattern may provide a help position for setting the cutting position, but it may also serve as a guide in the placement of toric intraocular lenses, or it may also be an aid in introducing a suture in a corneal transplant.
  • For the positioning of the mus- In the right place it is necessary to determine the position of the pupil on the eye to be treated. Ideally, the position is always redefined during the operation, so tracked, as it may come during the procedure to movements of the entire eye and thus the pupil.
  • the invention has for its object to develop a method for determining properties or determining and / or tracking the position of a characteristic eye component during an eye treatment or diagnosis, which works quickly and yet reliable.
  • the object is achieved according to the invention by a method for determining properties or determining and / or tracking the position of a characteristic eye component with the features of claim 1.
  • essential properties such as the radius or position, preferably of the center of characteristic ocular components, during an ocular examination or treatment are determined by looking for the characteristic ocular component in a first image taken by an ocular eye during ophthalmic treatment or diagnosis and giving it a characteristic size is derived.
  • This characteristic quantity is used to more quickly and easily locate the characteristic eye component in each additional image of the same eye taken with the same camera as part of the same eye examination or treatment.
  • the localization takes place in each case with methods of image processing, preferably a correlation method or an edge detection method or other known methods automatically.
  • the invention is based on the idea at the beginning of the eye examination or treatment, as long as it is not too time critical to claim a little more time to derive in a somewhat more complex but very reliable process step characterizing the ocular component size, which subsequently during The remaining course of the eye examination or treatment can be used to use in a then simplified method, this as a known size and thus faster derive the value of the eye component to be determined very quickly and just as reliably.
  • the same principle of an image processing method is used in the localization in the first image and in the tracking process in the localization in all subsequent images. That the localization takes place in each case with correlation, edge detection or a corresponding method, which was selected.
  • This has the advantage that only one method principle has to be programmed and the localization method and the tracking method only differ in that due to the consideration of the characteristic variable in the tracking method in this part of the method a part of the method can be skipped. The localization process is thus shortened and thus faster.
  • the limbus or pupil radius is derived as the characteristic variable, so that it is already known for the tracking method, ie for the second and each further localization of the characteristic eye component, how large the characteristic eye component to be sought is.
  • This advantageous idea is based on the knowledge that the size of the sought-after characteristic object only changes significantly in the course of the method when the recording conditions change, otherwise it remains approximately constant. An object in an image whose size is already known, is much easier and faster to find than an object of which nothing is known.
  • the radius of the characteristic ocular component is determined in a localization method in that the image detail to be analyzed in each case correlates with annular comparison objects of different radii becomes.
  • the best match for the comparison object is determined in each case and based on the comparison of the best match values the best among all absolutely optimal match and thus the comparison object determines the size of the characteristic object to be searched for.
  • the respective maximum response of the correlation function, which results in the correlation with the image section is plotted against the radius of the comparison object, resulting in a function which always forms a maximum when the radius is good to the radius of a circular or annular characteristic eye component in the image section fits.
  • the maximum which results at the largest radius belonging to a maximum value, corresponds to the radius of the largest annular object in the image detail and thus to the limbus radius; what was detected in the course of this procedure.
  • the determination of the radius based on the correlation with annular comparison objects of different sizes has proven to be a method which is superior to conventional edge detection methods, above all because it is extremely reliable and less susceptible to disturbances. Even if the surgeon covers a part of the eye with an instrument at the beginning of the procedure, the radius can be found reliably, since the annular character of the limbus or pupillary margin is maintained as long as the eye is not completely covered.
  • a particularly reliable, rapid and advantageous method for locating annular characteristic ocular components, such as the limbus or the pupil edge, is to convolve the image with an annular comparative object constructed of two concentric annular components between which folding occurs during folding ,
  • the comparison object or the filter has at least two components, the possibility arises in each case a component of the eye area outside the density transition, z.
  • the density transition can thus be strengthened to a certain extent via the convolution with the filter.
  • the optimal match with the template or filter, which are used depending on the method then arises when the inner ring of the comparison object z. B. on the Iris, the outer z. B. on the Sclera and thus the transition region is thus in this case includes the limbus of the two annular components.
  • the limbus center comes into coincidence with the center of the comparison object.
  • the comparison object may as well be composed of annular segments. It is only essential for the method that overall the annular character of the comparison object is maintained. Especially in the border area of the image, it is even better to use only ring segments. In the case of these ring segments, it is preferable to expose the region which lies at the edge at which the comparison object approaches the correlation and thus also the limbus in the image. With the correlation, the comparison object thus better corresponds to the object to be found, which, as soon as it reaches the edge area of the image, is likewise partially cut off.
  • This method has proved to be particularly advantageous for the near-real-time analysis of the further images of the eye detail, since it can be carried out extremely quickly by specifying a known radius for the comparative object to be correlated and because of the respective averaging which permits any detection of an annular object As soon as only the ring-shaped character is reasonably visible, even if a part of the ring is covered, it can be regarded as extremely reliable, especially in the later course of the operation, during which many surgeries are necessary and thus many disturbances affect the limbus.
  • a radius derived in a first localization method in all other tracking methods in which the same characteristic eye component is to be determined in the image section, but can also be used very advantageously if, for example, working with an edge detection method.
  • this is often followed by a Hough transformation in which ring-shaped objects are found in a picture binarized by means of edge detection, wherein the known radius can be used to check whether this is due to the Hough transformation determined annular object actually corresponds to the eye component to be sought.
  • this method is not accelerated, but at least reliable.
  • the color channel which is most suitable for carrying out the localization of the ocular components in the tracking procedure is determined as the characteristic variable, in particular when taking a multicolor digital image, and is used as the basis.
  • the color channel which is then used as the gray scale image for the localization process.
  • the respectively suitable color channel is generally the one in which the sought-after characteristic eye component, for example the limbus or the pupil edge, has the greatest density transition, ie the greatest contrast jump. This can also be a combination of multiple color channels.
  • This color channel is then advantageously used for all further localizations of the characteristic ocular component in the tracking procedure, in the analysis of all further recordings. It can be assumed that this color channel is also very suitable for the following shots and refrained from redefining it for each image. This significantly increases the speed of each tracking method used. Regardless of which algorithm is used, this makes it easier to provide real-time analysis.
  • the characteristic size which is determined after the one-time localization of the characteristic ocular component and repeatedly used in the further method is a threshold value.
  • Setting absolute thresholds for binarizing or segmenting a digital image is always extremely critical and often flawed. There is always a tightrope between leaving too much data and eliminating it for the evaluation of important data, especially with the big differences between eyes and especially between diseased eyes.
  • the iris is extremely bright, the pupil very dark - almost black - another time the pupil is light or milky due to a cataract and the iris can be dark brown, almost black. There are even cases in which the iris and pupil are nearly identical in color, which is why the determination of an absolute threshold is extremely error-prone and difficult, especially for these recordings.
  • the initial localization of a characteristic eye component such as the boundary between sclera and iris or between iris and pupil can advantageously be found by binarizing the digital image of the eye detail using an edge detection method and binarizing the image Hough transformation two nested circles are determined.
  • the Hough transform is a very suitable means of reliably finding the two transitions from which the center of the iris or pupil can subsequently be derived.
  • Performing Hough transforms is time consuming and therefore incapable of quickly analyzing all images taken during an eye exam or treatment, so that assistance can then be displayed in approximately the same image of the eye.
  • another method is advantageously used for tracking, ie for determining the position of the characteristic eye components in the following photographs.
  • the threshold is used to separate the pupil from the iris, thereby determining the pupil to determine its center.
  • This method can equally well be used for the sclera-iris border. It is only important that the threshold value used for the threshold value formation is derived from the first method step, in which the characteristic eye feature is determined by means of a Hough transformation, and that this threshold value is maintained for the further recordings. This method also makes it possible to ensure a very reliable localization of the characteristic visual components, at least for all follow-up images.
  • the characteristic variable which is used for all further recordings is preferably always automatically adapted when the recording conditions at the camera are changed.
  • the radius will be adjusted accordingly whenever the zoom factor on the camera is changed.
  • the color channel selection or threshold may need to be adjusted if the camera's shooting mode is changed. If, for example, the lighting or the sensitivity of the camera is changed, this can have a significant effect on the contrast conditions. In this case, it is very advantageous to make an adjustment.
  • this adaptation can also take place in that the localization method which is more time-consuming again is carried out and a new radius, threshold value or color channel is selected. However, this disrupts the procedure and leaves the surgeon unaided for a while.
  • FIG. 1 shows schematically an apparatus for carrying out the method according to the invention
  • FIG. 2 shows a flow chart for explaining an advantageous embodiment of the method according to the invention by means of a convolution with a ring filter
  • FIG. 3 shows an example of an advantageous ring filter superimposed on a receptacle of an eye cutout
  • Fig. 1 shows a schematic representation of the basic structure, as it is typical for an eye treatment in which the method according to the invention can be used particularly advantageously.
  • the patient's eye 1 to be treated which is illuminated by a light source (not shown), is observed firstly by means of an eyepiece 2 and secondly by means of a video camera 3, whereby the observation beam path is split by a beam splitter 4 into two observation beam paths for the observing instruments becomes.
  • the data recorded on the video camera 3 are transferred to a computing unit 5, where the data is stored and analyzed.
  • the pattern generation unit 6 can be embodied, for example, as a projector with an annular LED display which superimposes a pattern in the observation beam path of the eye via the beam splitter 4.
  • the eye 1 is continuously recorded digitally in very short time sequences with the camera 3, or analog data is converted into digital data and the digital data of the recording of the eye detail, as it is, for example, in Fig. 3 (to illustrate the comparison object with superimposed ring filter) can be seen, transmitted to the arithmetic unit 5.
  • the eye center and the limbus radius are determined, so that the optimum cutting position for the cut, for the removal of the clouded and for insertion of the artificial lens, can be determined.
  • the image seen by the surgeon's eye 7 through the eyepiece 2 is superimposed on a pattern generated at the pattern generating unit 6 indicating this cutting position.
  • the eye of the surgeon 7 always sees during the treatment the optimal cutting position for preparing the cut.
  • a first method step 8 the image of a section of an eye to be treated, as can be seen in FIG. 3, is recorded on the camera 3.
  • this image is folded on the arithmetic unit 5 with the ring filter 14 shown schematically in FIG.
  • the ring filter 14 includes two concentric rings 15 and 16, which are placed symmetrically in Fig. 3 around the examined limbus 17.
  • the ring filter 14 is normalized such that the outer ring 15 provides positive contributions to the filter response while the inner ring 16 gives negative contributions.
  • the ring filter 14 is normalized so that the filter response in the convolution with a gray area is zero. This means that the two rings 15 and 16 are weighted according to their area proportions in the image. This ring filter 14 is now folded at the beginning of the localization step 9 with the image detail, that is, the filter response is determined at each point of the image.
  • FIG. 4 The result of the convolution with a ring filter 14 as shown in FIG. 3, ie the filter response when the filter radius and the radius of the limbus 17 are approximately identical, is shown in FIG. 4 as an example.
  • the maximum filter response results, which is shown bright here.
  • the center of the bright area corresponds to the eye center and, as such, is transferred to the pattern generation unit 6. The exact determination of this However, the center is only possible if the radius of the limbus 17 or the radius of the most suitable ring filter 14 has been determined. At the beginning of the process step 9 this is still unknown.
  • a folding of the image section with ring filters 14 for a radius region to be examined is carried out in a method step 10.
  • the image is in each case folded with a ring filter 14 of another radius and determines the respective maximum filter response.
  • the resulting maximum filter responses are each plotted over the associated radius.
  • a curve results, as shown for example in FIG.
  • the curve shows a distinct peak. It is found out that the first pronounced maximum starting from the largest radius always represents the filter response, for a filter whose radius corresponds to the radius of the limbus 17. Therefore, the radius at which the first distinct maximum is seen is defined as the radius of the limbus 17.
  • the center of the limbus 17 corresponds to the location of the maximum filter response, which was determined in the case with the ring filter 14 whose radius corresponds to the radius of the limbus 17.
  • this radius of the limbus 17 is held on a memory unit, so that it is available for further processes.
  • a further image of the eye detail is taken, which is now to be analyzed as soon as possible, so that subsequently assistance for the surgeon can be superimposed into this image by means of a pattern generation unit 6.
  • a ring filter 14 whose radius corresponds to the radius stored in method step 11.

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  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Molecular Biology (AREA)
  • Biophysics (AREA)
  • Ophthalmology & Optometry (AREA)
  • Biomedical Technology (AREA)
  • Human Computer Interaction (AREA)
  • Medical Informatics (AREA)
  • Physics & Mathematics (AREA)
  • Surgery (AREA)
  • Animal Behavior & Ethology (AREA)
  • General Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Veterinary Medicine (AREA)
  • Eye Examination Apparatus (AREA)
  • Image Analysis (AREA)

Abstract

L'invention concerne un procédé permettant de déterminer des propriétés ou de déterminer et/ou de repérer la position d'une partie caractéristique de l'oeil pendant un examen ou un traitement de l'oeil. Selon l'invention, une image numérique d'au moins une coupe d'un oeil est enregistrée au moyen d'une caméra et la partie caractéristique de l'oeil est déterminée dans cette image à l'aide d'un procédé de traitement d'images et par un procédé de localisation. Dès que cette partie est connue, au moins une grandeur caractéristique de la partie de l'oeil déterminée est dérivée. Au moins une autre image numérique de la coupe de l'oeil est ensuite enregistrée au moyen de la même caméra et la partie de l'oeil est à nouveau localisée dans cette image par un procédé de poursuite. Dans ce procédé de poursuite, la grandeur caractéristique dérivée préalablement est prise en considération, ce qui permet d'accroître la fiabilité et/ou la rapidité de ce procédé.
PCT/EP2008/068107 2007-12-21 2008-12-19 Procédé pour déterminer des propriétés ou pour déterminer et/ou repérer la position d'une partie caractéristique de l'oeil Ceased WO2009080792A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
US12/801,689 US8662667B2 (en) 2007-12-21 2010-06-21 Ophthalmologic visualization system
US14/147,046 US9089283B2 (en) 2007-12-21 2014-01-03 Ophthalmologic visualization system

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102007055921A DE102007055921A1 (de) 2007-12-21 2007-12-21 Verfahren zur Ermittlung von Eigenschaften bzw. Ermittlung und/oder Verfolgung der Position des Zentrums charakteristischer Augenbestandteile
DE102007055921.8 2007-12-21

Related Parent Applications (1)

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PCT/EP2008/068108 Continuation-In-Part WO2009080793A1 (fr) 2007-12-21 2008-12-19 Système d'observation de l'oeil et procédé associé

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PCT/EP2008/068104 Continuation-In-Part WO2009080791A1 (fr) 2007-12-21 2008-12-19 Procédé de détection et/ou de suivi de la position de composants caractéristiques de l'oeil

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Cited By (2)

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US8308298B2 (en) 2009-06-24 2012-11-13 Carl Zeiss Meditec Ag Microscopy system for eye surgery
US8662667B2 (en) 2007-12-21 2014-03-04 Carl Zeiss Meditec Ag Ophthalmologic visualization system

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DE102009033931B4 (de) * 2009-07-20 2016-03-10 Carl Zeiss Meditec Ag Verfahren zur Ermittlung einer Größenveränderung und/oder Positionsveränderung eines ringförmigen Bestandteils eines Auges in einem Abbild

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US8662667B2 (en) 2007-12-21 2014-03-04 Carl Zeiss Meditec Ag Ophthalmologic visualization system
US9089283B2 (en) 2007-12-21 2015-07-28 Carl Zeiss Meditec Ag Ophthalmologic visualization system
US8308298B2 (en) 2009-06-24 2012-11-13 Carl Zeiss Meditec Ag Microscopy system for eye surgery

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