Topcon Corporation

Kabushiki Kaisha Topcon

Osaka University

Zhenguo Wang

Kinpui Chan

Zaixing Mao

Jongsik Kim

Yasufumi Fukuma

Makoto Fujino

Kazuhiro Oomori

Jonathan Liu

Charles A Reisman

Song Mei

Zhijia Yuan

Atsushi Kubota

Hideharu Suzuki

Toshihiro Mino

Bin Cao

Dawei Li

Ying Dong

Kohji Nishida

Richard F Spaide

Kazuichi Maruyama

Ryo Kawasaki

Chikako Hara

Atsuya Miki

Hirokazu Sakaguchi

Xin Sui

Kim Jongsik

A medical diagnostic apparatus includes a receiver circuit that receives three-dimensional volumetric data of a subject's eye, and a processor configured to separate portions of the three-dimensional volumetric data into separate segments, perform processing differently on each of the separate segments, and combine the separately processed segments to produce an enhanced three-dimensional volumetric data set. The processor is further configured to generate at least one diagnostic metric from the enhanced three-dimensional volumetric data set, and the processor is further configured to evaluate a pathological condition based on the at least one diagnostic metric. Related methods and computer readable media are also disclosed.

Medical diagnostic apparatus and method for evaluation of pathological conditions using 3D optical coherence tomography data and images

A method for thickness measurement of a multi-layer object combines frequency analysis and a theoretical model. The frequency analysis is used to determine the thickness of a thicker layer of the object. The theoretical model is used to determine the thickness of the thinner layer of the object.

2D multi-layer thickness measurement

An ophthalmologic apparatus includes an objective lens that faces a subject's eye, an illumination optical system that irradiates a cornea of the subject's eye with illumination light through the objective lens, and a corneal measurement optical system including an interference image capturing camera that takes an image of a corneal reflection light. The corneal reflection light is a reflection of the illumination light reflected from the cornea, through the objective lens. A numerical aperture G of the illumination optical system is larger than a numerical aperture g of the corneal measurement optical system.

Ophthalmologic apparatus

An ophthalmological imaging device includes illumination optics having an illumination light source that outputs an illumination light, a scanner that redirects the illumination light toward a portion of an object to be imaged, and an optical image capture device including a camera that receives backscattered light that is scattered from the illumination light by the object and captures first and second images of the backscattered light. The device also includes a control processor that controls the scanner and the optical image capture device to cause the optical image capture device to capture the first and second images of the object. The first and second images are captured by the camera at different times and extracted from different portions of the backscattered light. The device also includes an image processor that generates a stereoscopic image from the first and second images of the object.

Method and apparatus for stereoscopic color eye imaging

An ophthalmic apparatus includes an illumination optical system, an imaging optical system, and a controller. The illumination optical system is configured to generate illumination light using light from a light source, and to illuminate a changeable illumination region on a predetermined site of a subject's eye with the illumination light having a light intensity corresponding to a size of the illumination region. The imaging optical system is configured to guide returning light of the illumination light from the subject's eye to a light receiving surface of an image sensor. The controller is configured to control the image sensor to set an opening range so as to overlap an illumination range of the returning light on the light receiving surface corresponding to the illumination region and to capture a light receiving result obtained by a light receiving element in the set opening range.

Ophthalmic apparatus, method of controlling same, and recording medium

An ophthalmologic apparatus includes: an objective lens that faces a subject's eye; an alignment light emitting unit that irradiates the subject's eye with alignment light to perform measurement of alignment between the objective lens and the subject's eye; an alignment reflection light receiving unit that receives alignment reflection light, which is a reflection of the alignment light from the subject's eye; an anterior segment camera that receives corneal reflection light; and a holder positioned between the anterior segment camera and the objective lens to hold the anterior segment camera, wherein the holder includes an imaging transmissive portion that transmits the corneal reflection light to the anterior segment camera, a first light-transmissive portion that transmits the alignment light from the alignment light emitting unit, and a second light-transmissive portion that transmits the alignment reflection light from the subject's eye.

Ophthalmological device

Optical coherence tomography (OCT) angiography (OCTA) data is generated by one or more machine learning systems to which OCT data is input. The OCTA data is capable of visualization in three dimensions (3D) and can be generated from a single OCT scan. Further, motion artifact can be removed or attenuated in the OCTA data by performing the OCT scans according to special scan patterns and/or capturing redundant data, and by the one or more machine learning systems.

Method and apparatus for optical coherence tomography angiography

A low coherence imaging method comprises acquiring image data of an object with an interferometric imaging system, where the image data is from a location of the object at first and second times; determining a first depth profile from the image data from the location at the first time and a second depth profile from the image data of the location at the second time; determining a change with respect to depth between the first and second depth profiles; and determining a property, or identifying a location, of at least one dynamic particle in the object based on the change between the first and second depth profiles. The method is able to identify, analyze, and/or visualize dynamic particles with features comparable to at least fluorescein angiography, indocyanine green angiography, confocal scanning laser fluorescein angiography, confocal scanning laser indocyanine green angiography, and fluorescence microscopy images, without the use of a dye.

Method and apparatus for low coherence interferometry

A method for determining thickness of layers of the tear film includes reconstructing a full- or hyper-spectral interference pattern from an imaged multi-spectral pattern. Tear film thickness can then be estimated from the full- or hyper-spectral interference pattern. Using a full- or hyper-spectral interference pattern provides a greater number of frequency sampling points for increased tear film thickness estimation accuracy, without traditional time consuming techniques.

2D multi-layer thickness measurement with reconstructed spectrum

An interferometric method of identifying the thickness of an object that is too thin to be resolved by a Fourier transform of the interference signal includes applying a harmonic frequency modulation to an envelope of the interference signal. Where the object is a tear film, this method may be utilized to determine a thickness of the lipid layer of the tear film.

Method and apparatus for measuring tear film thickness using optical interference

An ophthalmologic apparatus includes: an objective lens that faces a subject's eye; a first illumination optical system that irradiates a cornea of the subject's eye with illumination light; and a corneal measurement optical system having an imaging element that takes an image of a corneal reflection light, which is a reflection of the illumination light, through the objective lens, and outputs an imaging signal. The corneal measurement optical system includes a first mirror arranged near the objective lens and a second mirror arranged near the imaging element. The first and second mirrors and are configured such that the corneal reflection light that enters and is reflected from the first mirror, and then enters and is reflected from the second mirror exits toward an incident side from which the corneal reflection light enters a reflection surface of the first mirror.

Methods and systems for angiographic imaging with optical coherence tomography (OCT) are described using ratio-based and angiographic deviation based calculations. In using these calculations to determine motion, arbitrary interframe permutations may be used, post- calculated, non-linear results for projection visualization may be averaged, poor matches may be eliminated on an A-line by A-line basis, windowing functions may be used to improve results, partial spectrums may be used when capturing data, and a minimum intensity threshold may be used for determining which pixels to use.

OCT angiography calculation with optimized signal processing

Shadows caused by opacities and obstructions (such as blood vessels) can block detection of structural information of objects below the shadow-causing structure, affecting visualization and analysis of those deeper structures. An image processing method for removing these shadows includes applying a low pass filter to an energy profile of an image to remove high frequency fluctuations in energy, thereby effectively recovering lower energy inside shadow regions and removing high frequency speckle. The image is then adjusted, for example by linear scaling, based on the filtered energy profile. Two dimensional filters may also be applied for volumes.

3D shadow reduction signal processing method for optical coherence tomography (OCT) images

A machine learning model is trained to identify the texture difference between the different layers of a multilayer object. By training with data in full 3D space, the resulting model is capable of predicting the probability that each pixel in a 3D image belongs to a certain layer. With the resulting probability map, comparing probabilities allows one to determine boundaries between layers, and/or other properties and useful information such as volume data.

3D quantitative analysis with deep learning

Ophthalmological images generated by coherent imaging modalities have multiple types of noise, including random noise caused by the imaging system and speckle noise caused by turbid objects such as living tissues. These noises can occur at different levels in different locations. A noise-reduction method and system of the present disclosure thus relates to applying different filters for different types of noise and/or different locations of images, sequentially or in parallel and combined, to produce a final noise-reduced image.

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Ridgewood, NJ, United States of America

Zhenguo Wang