Singapore Health Services Pte Ltd

Agency for Science, Technology and Research

National University of Singapore

Plano Pte Ltd

Tien Yin Wong

Jiang Liu

Wing Kee Damon Wong

Ngan Meng Tan

Beng Hai Lee

Jun Cheng

Joo Hwee Lim

Huiqi Li

Zhuo Zhang

Fengshou Yin

Tin Aung

Baskaran Mani

Carol Cheung

Michael Belkin

R Manjunatha Kini

Yong Liu

Mong Li Lee

Wynne Hsu

Ziyang Liang

Yanwu Xu

Jodhbir Singh Mehta

Xinting Gao

Tiang Hwee Donald Tan

Wing Kee Wong

Veluchamy Amutha Barathi

Xiaoqin Fang

Dejiang Xu

Yim Lui Cheung

Dan Belkin

Yim-lui Carol Cheung

Ching-Yu Cheng

Xiangang Cheng

Shu Wei Daniel Ting

Gilbert Lim

Gemmy Chui Ming Cheung

Ge Ruowen

Rajamani Lakshminarayanan

Mohamed Dirani

Shaohua Li

Daniel Shu Wei Ting

Gavin Siew Wei Tan

Chui Ming Gemmy Cheung

Rick Siow Mong Goh

Disclosed is a method for training a neural network to quantify the vessel calibre of retina fundus images. The method involves receiving a plurality of fundus images; pre-processing the fundus images to normalise images features of the fundus images; and training a multi-layer neural network, the neural network comprising of a convolutional unit, multiple dense blocks alternating with transition units for down-sampling image features determined by the neural network, and a fully-connected unit, wherein each dense block comprises a series of cAdd units packed with multiple convolutions, and each transition layer comprises a convolution with pooling.

Retina vessel measurement

A method and apparatus for monitoring arid for improving eye health of a user of a device, the method comprising receiving m indication that an event occurred associated with rise of the device; updating data on the device according to the data included in a user profile associated with a user; generating a personalized user interface and displaying said interface on the device; detecting a distance of the user from the device; and providing an indication once the distance exceeds a predefined threshold for a predefined time period.

Apparatus and method for monitoring use of a device

This disclosure provides methods of a method of treating a retinal angiogenic in a subject comprising administering an effective amount of an Angio-3 peptide.

Angio-3 for treatment of retinal angiogenic diseases

A method of modifying a retina fundus image for a deep learning model is disclosed. In a described embodiment, the method includes converting a retina fundus image to a binary image by converting pixels of the retina fundus image to low intensity modified pixels and high intensity modified pixels of the binary image, and determining a first boundary between the low intensity modified pixels and high intensity modified pixels of the binary image. The method further includes removing outlier boundary values from the first boundary, constructing a second boundary from remaining boundary values, identifying the pixels of the retina fundus image that are within the second boundary, and constructing a modified retina fundus image containing the identified pixels for a deep learning model.

Method of modifying a retina fundus image for a deep learning model

A method is proposed for automatically locating the optic disc or the optic cup in an image of the rear of an eye. A portion of the image containing the optic disc or optic cup is divided into sub-regions using a clustering algorithm. Biologically inspired features, and optionally other features, are obtained for each of the sub-regions. An adaptive model uses the features to generate data indicative of whether each sub-region is within or outside the optic disc or optic cup. The result is then smoothed, to form an estimate of the position of the optic disc or optic cup.

Methods and systems for automatic location of optic structures in an image of an eye, and for automatic retina cup-to-disc ratio computation

A non-stereo fundus image is used to obtain a plurality of glaucoma indicators. Additionally, genome data for the subject is used to obtain genetic marker data relating to one or more genes and/or SNPs associated with glaucoma. The glaucoma indicators and genetic marker data are input into an adaptive model operative to generate an output indicative of a risk of glaucoma in the subject. In combination, the genetic indicators and genome data are more informative about the risk of glaucoma than either of the two in isolation. The adaptive model may be a two-stage model, having a first stage in which individual genetic indicators are combined with respective portions of the genome data by first adaptive model modules to form respective first outputs, and a second stage in which the first outputs are combined by a second adaptive mode. Texture analysis is performed on the fundus images to classify them based on their quality, and only images which are determined to meet a quality criterion are subjected to an analysis to determine if they exhibit glaucoma indicators. Also, the images are put into a standard format. The system may include estimating the position of the optic cup by combining results from multiple optic cup segmentation techniques. The system may include estimating the position of the optic disc by applying edge detection to the funds image, excluding edge points that are unlikely to be optic disc boundary points, and estimating the position of an optic disc by fitting an ellipse to the remaining edge points.

Obtaining data for automatic glaucoma screening, and screening and diagnostic techniques and systems using the data

An OCT image of an eye which has been subject to a DSAEK corneal transplant, in which a Descement's membrane in the cornea has been replaced by a graft, is processed to identify the outline of the graft. The process includes the steps of: computationally extracting the boundary of the cornea including the graft; computationally detecting the corners of the graft; computationally extracting points on the boundary between the graft and the original cornea; and computationally fitting the points on the boundary between the graft and the original cornea smoothly into a curve. The outline of the graft is then displayed. A graft profile may be generated, indicating the thickness of the graft at each point along its length.

Corneal graft evaluation based on optical coherence tomography image

A two-dimensional retinal fundus image of the retinal fundus of an eye is processed by optic disc segmentation () followed by cup segmentation. Data derived from the optic disc segmentation (i.e. the output of the disc segmentation () and/or data derived from the output of the optic disc segmentation step, e.g. by a smoothing operation) and data derived from the out-put of the optic cup segmentation (i.e. the output of the cup segmentation () and/or data derived from the output of the optic disc segmentation, e.g. by a smoothing operation) are fed () to an adaptive model which has been trained to generate from such inputs a value indicative of cup-to-disc ratio (CDR) of the eye. The CDR is indicative of glaucoma. Thus, the method can be used to screen patients for glaucoma.

Automatic cup-to-disc ratio measurement system

A platform is proposed for automated analysis of retinal images, for obtaining from them information characterizing retinal blood vessels which may be useful in forming a diagnosis of a medical condition. A first aspect of the invention proposes that a plurality of characteristics of the retina are extracted, in order to provide data which is useful for enabling an evaluation of cardiovascular risk prediction, or even diagnosis of a cardiovascular condition. A second aspect uses fractal analysis of retinal images to provide vascular disease risk prediction, such as, but not limited to, diabetes and hypertension.

Retinal image analysis systems and methods

A method for determining the position of an optic cup boundary in a 2D retinal image. The method includes detecting kinks in blood vessels at an estimated boundary of the optic cup and the optic disc, and determining the position of the optic cup boundary in the 2D retinal image based on the detected kinks. The determined optic cup boundary may be used for determining a CDR which may in turn be used for determining a risk of contracting glaucomatous.

Method and system for determining the position of an optic cup boundary

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Singapore, Singapore

Tien Yin Wong