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A Macular Localization Method Based on Improved Faster R-CNN

A positioning method and macular technology, applied in image analysis, image enhancement, instruments, etc., can solve the problems of algorithm failure, easy to be interfered by noise, poor shooting effect, etc.

Active Publication Date: 2021-06-15
SUZHOU UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The current macular localization algorithm mainly has the following defects: (1) it is very dependent on the information of the optic disc and blood vessels, and has certain application limitations due to the influence of the detection accuracy of the optic disc and blood vessels; (2) due to the use of morphological features, Therefore, some traditional methods are usually easily disturbed by noise. When the macular area is greatly deformed or the shooting effect is not good, the existing algorithm will fail

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  • A Macular Localization Method Based on Improved Faster R-CNN
  • A Macular Localization Method Based on Improved Faster R-CNN
  • A Macular Localization Method Based on Improved Faster R-CNN

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Embodiment Construction

[0030] The technical solutions of the various embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Apparently, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts fall within the protection scope of the present invention.

[0031] The present invention provides a kind of macular localization method based on improved Faster R-CNN, comprises the following steps:

[0032] S1. Collect training samples: obtain fundus images from the Kaggle dataset, mark the macula area on the obtained fundus images, and make the marked images into the format of the VOC2007 dataset to construct a training sample set;

[0033] S2. Building a network model: building a CNN feature extraction network, a cascaded region proposa...

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Abstract

The invention discloses a macular positioning method based on the improved Faster R-CNN, which includes collecting training samples, constructing a network model, training the network model, constructing a detection model, and detecting and positioning the macula. The present invention uses the improved Faster R-CNN to effectively locate the macular area, reduces the influence of the optic disc and blood vessels on the macular area, and has strong anti-noise interference ability, which greatly improves the accurate positioning of the macular area. Processing lays the groundwork.

Description

technical field [0001] The invention belongs to the technical field of retinal image processing and analysis methods, in particular to the positioning of a target region of a retinal fundus color photo image, and in particular to a macular positioning method based on an improved Faster R-CNN. Background technique [0002] Fundus color photo technology has been widely used in the clinical examination of fundus-related diseases, and has received more and more attention and attention. For example: diabetic macular edema (DME), the leading cause of blindness in diabetic patients, age-related macular degeneration (AMD), the leading cause of blindness in adults, central serous chorioretinopathy (central serous chorioretinopathy, CSC) is the main cause of eye diseases in most young and middle-aged men. Therefore, early disease detection is very important for disease prevention and treatment. If these macular diseases are not detected and treated in time, they will lead to permane...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06T7/73G06K9/62
CPCG06T7/0012G06T7/73G06T2207/10004G06T2207/10024G06T2207/20084G06T2207/20081G06T2207/30041G06F18/2413
Inventor 陈新建黄旭东朱伟芳
Owner SUZHOU UNIV