Method and device for retinal image analysis
AssigneeThe Chinese University of Hong Kong
InventorsBenny Chung-Ying Zee, Jack Jock-Wai Lee, Esther Qing Li
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Abstract
The present application provides methods and devices for diagnosing and/or predicting the presence, progression and/or treatment effect of a disease characterized by retinal pathological changes in a subject.
Claims55
A method for diagnosing and/or predicting the presence, progression and/or treatment effect of a disease characterized by retinal pathological changes in a subject, comprising the steps of:
- (a) obtaining a retinal fundus image from the subject;
- (b) converting the image to a gray level image and/or extracting vessels from the image to obtain the gray level image and/or the vessel image;
- (c) performing statistical texture analysis on the gray level image and/or the vessel image, and generating one or more factors, wherein the statistical texture analysis includes using gray level co-occurrence matrix (GLCM) and/or run length matrix (RLM) to obtain texture features, including normalized Homogeneity, normalized Entropy, normalized Contrast, normalized 4th moment and normalized Run percentage;
- (d) comparing the one or more factors obtained from step (c) with those of a control, a change of the factors is an indication of the presence, progression and/or treatment effect of the disease in the subject.
A method for generating one or more factors associated with retinal pathological changes in a disease of a subject, comprising the steps of:
- (a) obtaining a retinal fundus image from the subject;
- (b) converting the image to a gray level image and/or extracting vessels from the image to obtain the gray level image and/or the vessel image;
- and
- (c) performing statistical texture analysis on the gray level image and/or the vessel image, and generating one or more factors, wherein the statistical texture analysis includes using gray level co-occurrence matrix (GLCM) and/or run length matrix (RLM) to obtain texture features, including normalized Homogeneity, normalized Entropy, normalized Contrast, normalized 4th moment and normalized Run percentage.
A device for diagnosing and/or predicting the presence, progression and/or treatment effect of a disease characterized by retinal pathological changes in a subject, comprising:
- an image-capturing module for obtaining a retinal fundus image from the subject;
- a conversion module for converting the image to a gray level image and/or extracting vessels from the image to obtain said gray level image and/or vessel image;
- and
- an analysis module comprising a statistical texture analysis submodule for performing analysis on the gray level image and/or vessel image and generating one or more factors, wherein the statistical texture analysis submodule is configured to carry out gray level co-occurrence matrix (GLCM) and/or run length matrix (RLM) to obtain texture features, including normalized Homogeneity, normalized Entropy, normalized Contrast, normalized 4th moment and normalized Run percentage.
Dependencies are inferred from the claim text.