Cerebral infarction classification method based on deep learning

A technology of deep learning and classification methods, applied in the field of medical image recognition, can solve problems such as time-consuming and labor-intensive, and achieve a strong universal effect

Pending Publication Date: 2020-09-01
HANGZHOU DIANZI UNIV
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AI Technical Summary

Problems solved by technology

[0003] In the medical field, researchers still use traditional algorithms to analyze and process images. Even if it can meet the precision requirements of medical processing, it is very time-consuming and labor-intensive, requiring many experts to analyze and study images. Due to

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  • Cerebral infarction classification method based on deep learning
  • Cerebral infarction classification method based on deep learning
  • Cerebral infarction classification method based on deep learning

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Embodiment Construction

[0026] In order to make the above-mentioned features and advantages of the present invention more comprehensible, the following specific embodiments are described in detail in conjunction with the accompanying drawings.

[0027] The present invention provides a method for classifying cerebral infarction based on deep learning, such as figure 1 As shown, the method includes a training phase and a testing phase; the training phase includes the following steps:

[0028] In the first step, a doctor with experience in cerebral infarction selects the original data of cerebral infarction and normal brain, specifically extracts corresponding CT and MR medical image information from DICOM medical images, and stores them in JPG format. As the initial training data set, the ratio of normal brain and cerebral infarction in the training data set is 1:1, and the ratio of MR and CT in the data of normal brain and cerebral infarction is 1:1. The ratio of normal and cerebral infarction is als...

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Abstract

The invention provides a cerebral infarction classification method based on deep learning. According to the method, the concept of deep learning is utilized, different tasks are calculated in parallelthrough the network, feature fusion is carried out on features extracted by the network in a subsequent feature layer, and therefore classification in the aspect of cerebral infarction is carried outthrough the fused features. According to the method, the information is fully utilized by utilizing the characteristic that the CT information and the MR information can complement each other, and meanwhile, the information is fused on a subsequent characteristic layer, so that redundant information is removed, computing resources of a computer are reduced, and the cerebral infarction detection precision is improved.

Description

technical field [0001] The present invention relates to the field of medical image recognition, in particular to a method for merging medical images using a deep learning method to classify cerebral infarction. Background technique [0002] Cerebral infarction, also known as ischemic stroke, is called stroke or stroke in traditional Chinese medicine. The disease is caused by a variety of causes of blood supply disturbance in the local brain tissue, leading to ischemic and hypoxic lesions and necrosis of the brain tissue, resulting in clinically corresponding neurological deficits. According to different pathogenesis, cerebral infarction is divided into main types such as cerebral thrombosis, cerebral embolism and lacunar infarction. Cerebral thrombosis is the most common type of cerebral infarction. [0003] In the medical field, researchers still use traditional algorithms to analyze and process images. Even if it can meet the precision requirements of medical processing,...

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Application Information

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IPC IPC(8): G06T7/00G06K9/62G06N3/04G06N3/08G16H50/20G16H30/20
CPCG06T7/0012G06N3/08G16H50/20G16H30/20G06T2207/10081G06T2207/10088G06T2207/30016G06T2207/20081G06T2207/20084G06N3/045G06F18/241
Inventor 颜成钢谢益峰孙垚棋张继勇张勇东
Owner HANGZHOU DIANZI UNIV
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