# US 2023/0274451 A1 · Method of obtaining a complete shape of a crystalline lens from in-vivo measurements taken by optical imaging techniques and method of estimating an intraocular lens position from the complete shape of the crystalline lens in a cataract surgery

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- Number: US 2023/0274451 A1
- Document ID: US20230274451A1
- Status: Published application
- Kind: A1
- Application number: 17/923,993
- Filed: 2021-05-10
- Published: 2023-08-31
- Earliest claimed: 2020-05-08
- Assignees: Consejo Superior de Investigaciones Cientificas
- Applicants: Consejo Superior De Investigaciones CientíFicas
- Inventors: Eduardo MARTÍNEZ ENRÍQUEZ; Susana MARCOS CELESTINO
- Web page: https://patentgrep.com/patent/US20230274451A1

## CPC

- G06T 7/149: involving deformable models, e.g. active contour models
- G06T 7/50: Depth or shape recovery
- A61B 3/102: {for optical coherence tomography [OCT]}
- A61B 3/1173: {for examining the eye lens}
- A61B 34/10: Computer-aided planning, simulation or modelling of surgical operations
- G06T 7/0012: {Biomedical image inspection}
- G06T 7/60: Analysis of geometric attributes
- G06T 7/70: Determining position or orientation of objects or cameras (camera calibration G06T7/80)
- A61B 2034/108: {Computer aided selection or customisation of medical implants or cutting guides}
- G06T 2207/10101: Optical tomography; Optical coherence tomography [OCT]
- G06T 2207/20076: Probabilistic image processing
- G06T 2207/30041: Eye; Retina; Ophthalmic
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)

## Abstract

A method estimates a full shape of a crystalline lens from measurements of the lens taken in-vivo by optical imaging techniques and include visible portions of the lens. The method includes receiving the in-vivo measurements of the lens, determining non-visible portions of the lens parting from the in-vivo measurements. Determining non-visible portions of the lens includes establishing a location of points which define an initial full shape of a crystalline lens, displacing these points by lengths following a directions to a location of a second set of points, which are estimated points of the full shape of the lens. The initial full shape of a crystalline lens is obtained from ex-vivo measurements and the lengths is estimated from the in-vivo measurements. A further method selects an intraocular lens implantable in an eye. Yet further, a data-processing system configured to determines a full shape of a crystalline lens.

## Claims

### Claim 1

A method of estimating a full shape of a crystalline lens from measurements of the lens taken in-vivo by optical imaging techniques, the measurements comprising visible portions of the lens, the method comprising the steps of:
receiving, by a data-processing system, the in-vivo measurements of the lens,
determining, by the data-processing system, non-visible portions of the lens parting from the in-vivo measurements, the method characterized in that the step of determining non-visible portions of the lens comprises:
(a) establishing a location of a first plurality of points which defines an initial full shape of a crystalline lens,
(b) displacing the first plurality of points a plurality of lengths following a plurality of directions to a location of a second plurality of points,
wherein the second plurality of points are estimated points of the full shape of the lens of which the in-vivo measurements have been taken,
wherein the initial full shape of a crystalline lens is obtained from ex-vivo measurements, and the plurality of lengths is estimated from the in-vivo measurements.

### Claim 2 (depends on 1)

The method of claim 1,
wherein displacing the first plurality of points a plurality of lengths following a plurality of directions to a location of a second plurality of points comprises displacing according to at least one lens deformation pattern,
wherein the at least one lens deformation pattern is obtained from ex-vivo measurements.

### Claim 3 (depends on 2)

The method of claim 2, wherein each lens deformation pattern defines a ratio for each pair of points which are displaced according to the lens deformation pattern, each ratio being a ratio between a length of displacement of a point of the pair of points and a length of displacement of the other point of the pair of points.

### Claim 4 (depends on 2)

The method of claim 2, wherein the plurality of lengths of step (b) are obtained by applying a weight coefficient to each of the at least one lens deformation pattern, wherein the at least one weight coefficient is estimated from the in-vivo measurements.

### Claim 5 (depends on 4)

The method of claim 4, wherein the step of displacing the first plurality of points is performed according to the equation:
l
=
l
0
+
∑
k
K
a
k
⁢
e
k
wherein
l is a matrix which contains coordinates of the second plurality of points resulting from displacing the first plurality of points;
l0 is a matrix which contains coordinates of the first plurality of points;
ek is a matrix which defines a k lens deformation pattern of the at least one lens deformation pattern, the ek matrix defining displacements of the first plurality of points;
ak is a k scalar weight coefficient of the at least one weight coefficient;
K is a total number of lens deformation patterns used to estimate the full shape of the lens.

### Claim 6 (depends on 5)

The method of claim 5,
wherein each lens deformation pattern is an eigenvector of a covariance matrix of residual data,
wherein the residual data are a difference between a full shape of each lens of a set of ex-vivo lenses and an average full shape of the set of ex-vivo lenses.

### Claim 7 (depends on 4)

The method of claim 4,
wherein each weight coefficient applied to each lens deformation pattern is estimated from at least one secondary coefficient wherein each of the at least one secondary coefficient is a coefficient applied to a deformation pattern of a central anterior portion and of a central posterior portion of a full shape of a crystalline lens,
the method further comprising the step of:
calculating the at least one secondary coefficient applied to a deformation pattern of a central anterior portion and of a central posterior portion of a full shape of a crystalline lens;
wherein the at least one deformation pattern of a central anterior portion and of a central posterior portion is obtained from ex-vivo measurements; and
wherein the at least one secondary coefficient is calculated from the in-vivo measurements.

### Claim 8 (depends on 4)

The method of claim 4, the method further comprising the step of
estimating the at least one weight coefficient as a function of estimated geometric parameters of the lens measured in-vivo, the estimated geometric parameters being estimated from the in-vivo measurements, and the geometric parameters being characteristic geometric parameters of a shape of a lens such as lens thickness, radius of curvature of an anterior surface of the lens, radius of curvature of a posterior surface of the lens or Zernike coefficients describing surfaces of the lens.

### Claim 9 (depends on 4)

The method of claim 4, wherein a lens volume or a lens surface area or a lens diameter or an equatorial position is estimated as a function of the at least one weight coefficient.

### Claim 10 (depends on 1)

The method of claim 1, further comprising the step of
selecting an intraocular lens implantable in an eye by predicting an estimated lens position of the lens implantable in the eye,
wherein the estimated lens position is obtained from the full shape of the in-vivo measured lens.

### Claim 11 (depends on 10)

The method of claim 10, wherein the plurality of lengths of step (b) are obtained by applying a weight coefficient to each of the at least one lens deformation pattern, wherein the at least one weight coefficient is estimated from the in-vivo measurements and wherein the estimated lens position of a lens implantable in an eye is obtained using the following formula:
ELP
=
C
0
+
∑
k
K
a
k
⁢
C
k
wherein
ELP is the estimated lens position;
ak is a k scalar weight coefficient of the at least one weight coefficient;
Ck is a k positioning weight coefficient;
C0 is a bias term.

### Claim 12

A method of estimating a full shape of a crystalline lens from measurements of the lens taken by optical imaging techniques, the method comprising:
(a) estimating at least one weight coefficient from the measurements;
(b) applying a lens deformation pattern to each at least one weight coefficient to obtain a plurality of lengths of displacement, wherein the at least one lens deformation pattern is obtained from ex-vivo measurements;
(c) displacing a first plurality of points the plurality of lengths of displacement obtained in step (b) to a location of a second plurality of estimated points of the full shape of a lens.

### Claim 13

A data-processing system configured to determine a full shape of a crystalline lens by means of displacing a first plurality of points a plurality of lengths following a plurality of directions to a location of a second plurality of points, wherein
the first plurality of points defines an initial full shape of a crystalline lens, the initial full shape is obtained from ex-vivo measurements, and the plurality of lengths is obtained by applying a weight coefficient to each of at least one lens deformation pattern.

### Claim 14

canceled.

### Claim 15 (depends on 13)

The data-processing system of claim 13, comprising processing means for generating a realistic full shape of a crystalline lens, wherein the realistic full shape of a crystalline lens is defined by assigning values to the at least one weight coefficient, wherein the value of each of the at least one weight coefficient is within a minimum and a maximum values obtained from the ex-vivo measurements.

### Claim 16 (depends on 15)

The data-processing system of claim 15, wherein the values assigned to the at least one weight coefficient are randomly taken from a probability distribution selected from a number of predetermined probability distributions, wherein each probability distribution of the number of predetermined probability distributions is for a particular age range.

### Claim 17 (depends on 3)

The method of claim 3, wherein the plurality of lengths of step (b) are obtained by applying a weight coefficient to each of the at least one lens deformation pattern, wherein the at least one weight coefficient is estimated from the in-vivo measurements.

### Claim 18 (depends on 17)

The method of claim 17, wherein the step of displacing the first plurality of points is performed according to the equation:
l
=
l
0
+
∑
k
K
a
k
⁢
e
k
wherein
l is a matrix which contains coordinates of the second plurality of points resulting from displacing the first plurality of points;
l0 is a matrix which contains coordinates of the first plurality of points;
ek is a matrix which defines a k lens deformation pattern of the at least one lens deformation pattern, the ek matrix defining displacements of the first plurality of points;
ak is a k scalar weight coefficient of the at least one weight coefficient;
K is a total number of lens deformation patterns used to estimate the full shape of the lens.