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Fundus image microaneurysm identification method based on R-CNN

A fundus image and recognition method technology, applied in the field of medical image recognition, can solve problems such as inaccuracy and roughness

Active Publication Date: 2019-09-24
NANJING UNIV OF POSTS & TELECOMM
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  • Abstract
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Problems solved by technology

However, many pictures in the real world usually contain more than one object. At this time, if you use an image classification model to assign a single label to an image, it is actually very rough and not accurate.

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Embodiment Construction

[0046] The following will clearly and completely describe the technical solutions in the embodiments of the application with reference to the drawings in the embodiments of the application. Apparently, the described embodiments are only some of the embodiments of the application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application. The relevant directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship between the components in a certain posture (as shown in the drawings). Sports conditions, etc., if the specific posture changes, the directional indication will also change accordingly.

[0047] As mentioned in the background, target detection is one of the important problems in the field of m...

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Abstract

A fundus microaneurysm target detection model based on an R-CNN architecture realizes detection and identification of a fundus microaneurysm focus, and the method comprises the following steps: preprocessing a fundus image; carrying out blood vessel segmentation on the preprocessed image; performing three steps of local adaptive threshold segmentation, blood vessel removal and area screening on the preprocessed image to obtain a real microaneurysm candidate region; expanding the number of training samples by adopting data enhancement; using a transfer learning method, using a pre-trained VGG16 network for carrying out feature extraction on a sample, and adding a microaneurysm classifier behind the feature extraction network for joint training. According to the scheme, a new method is provided for diabetic retina image fundus microaneurysm target detection.

Description

technical field [0001] The invention belongs to the technical field of medical image recognition, in particular to a fundus microaneurysm target detection method based on an R-CNN architecture. Background technique [0002] Diabetes is a disease with a high incidence in modern people, and in recent years, the incidence of diabetes has become younger and younger. One of the most common complications of vascular injury caused by diabetes is diabetic retinopathy (Diabetic Retionopathy, DR), also known as diabetic retinopathy. Ophthalmology experts said that if diabetic patients can be diagnosed and treated effectively in the early stage of the disease, the patients can basically be cured to avoid loss of vision. Since patients with diabetes in the early stage do not have obvious visual symptoms, it is recommended that diabetic patients need to undergo a certain number of diabetes screenings every year to detect symptoms of diabetes in time. In the early fundus images of diabe...

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Application Information

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IPC IPC(8): G06K9/34G06K9/54G06K9/62G06T7/00G06T7/136
CPCG06T7/136G06T7/0012G06T2207/10004G06T2207/20081G06T2207/30101G06T2207/30096G06V10/267G06V10/20G06F18/214
Inventor 王子豪陈可佳张伶俐李孝展
Owner NANJING UNIV OF POSTS & TELECOMM
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