A macular location method based on improved Faster R-CNN

A positioning method and macular technology, applied in image data processing, instrument, character and pattern recognition, etc., can solve problems such as being susceptible to noise interference, poor shooting effect, algorithm failure, etc., to achieve strong anti-noise interference ability, avoid Gradient disappears, improving the effect of accurate positioning

Active Publication Date: 2019-02-22
SUZHOU UNIV
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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 location method based on improved Faster R-CNN
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  • A macular location method based on improved Faster R-CNN

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[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 location method based on improved Faster R-CNN, which includes collecting training samples, constructing a network model, training the network model, constructing a detection model and performing macular detection and location. The invention utilizes the improved Faster R-CNNto achieve effective localization of macular region, reduces the influence of optic disc and blood vessel on macular region and has strong anti-noise ability, which greatly improves the accurate localization of macular region and lays a foundation for the subsequent analysis and processingof fundus images.

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...

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Application Information

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Patent Type & Authority Applications(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
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