Automatic heart disease detection system based on convolutional neural network

Abstract

The present invention provides an automatic heart disease detection system based on a convolutional neural network. The automatic heart disease detection system comprises a database, a lesion information processing module, a key frame extraction module, a data cleaning module, an information fusion and storage module, a convolutional neural network learning module, a model storage and screening module and a lesion detection module. The invention relates to the fields of deep learning, medical treatment and computer vision. By design of scientific optimization, a set of automatic intelligent detection system for coronary artery calcification, complete occlusion and thrombosis based on the convolutional neural network is created and achieved, aiming at the requirements of diagnosis on resultaccuracy and timeliness, the design structure is ingenious, a high-quality auxiliary diagnosis detection result can be output without any manual assistance, and convenience is brought to coronary artery patients and doctors.

Description

technical field [0001] The present invention relates to the technical field of detection devices for cardiac lesions, in particular to an automatic detection system for cardiac lesions based on a convolutional neural network. Background technique [0002] Coronary artery disease is a disease that seriously endangers human health. It has high mortality, high disability rate, and high morbidity. Even if the medical level has improved, coronary artery disease will still bring great trauma to patients. About 15 million people in the world die from this disease, ranking first among all causes of death; [0003] At present, the use of coronary angiography imaging technology is the main method for coronary artery examination and diagnosis. However, the analysis of angiography images requires a large number of professional medical personnel, and they also have high requirements for their medical experience and professional quality; and At the same time, no matter how professional a...

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Problems solved by technology

[0010] In order to overcome the above-mentioned deficiencies in the prior art, the present invention provides an automatic detection system for cardiac lesions based on convolutional neural networks, which involves the fields of deep learning, medical treatment, and computer vision, and is mainly aimed at the time-consuming and laborious diagnosis of coronary artery lesions in artificial hearts. And the problem of low accuracy, through scientifically optimized design, created and realized a set of automatic intelligent detection system for coronary artery calcification, complete occlusion and thrombosis based on convolutional neural network, aiming at the accuracy and timeliness of diagnosis results The design structure is ingenious, and it can output high-quality auxiliary diagnostic test results without any manual assistance, bringing convenience to coronary artery patients and doctors

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