Cardiovascular vulnerable plaque recognition method and system based on attention model and multi-task neural network

A technology of attention model and vulnerable plaque, which is applied in the field of medical image processing, can solve the problems of low precision, OCT image recognition method recall rate, accuracy rate and coincidence degree are not high, and cannot meet actual needs, and achieve high precision , Strong practicability and simple operation

Active Publication Date: 2018-09-04
XI AN JIAOTONG UNIV
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Problems solved by technology

[0005] definition Set the initial value of nTP, nFP, nFN to 0; sequentially judge the detection area from 1 to M, if any B i , B j All are judged as errors and do not participate in the following calculations; if B i with any A k If there is an intersection, and the DSC value is greater than 0.5, it is considered that the target i is detected correctly, Ntp++, and the DSC value is less than or equal to 0.5, it is considered that the target i is detected incorrectly, nFP++; sequentially judge the real dete

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  • Cardiovascular vulnerable plaque recognition method and system based on attention model and multi-task neural network
  • Cardiovascular vulnerable plaque recognition method and system based on attention model and multi-task neural network
  • Cardiovascular vulnerable plaque recognition method and system based on attention model and multi-task neural network

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[0044] The present invention is described in further detail below in conjunction with accompanying drawing:

[0045] refer to figure 1 , the cardiovascular vulnerable plaque recognition system based on the attention model and multi-task neural network of the present invention includes a subsystem that removes noise in the original polar coordinate image based on the top-down attention model; The neural network performs a classification and segmentation subsystem on the vulnerable plaque image in the preprocessed image, and a region refinement subsystem on the classified and segmented vulnerable plaque image. The output of the subsystem based on the top-down attention model to eliminate the noise in the original polar coordinate image is to classify and segment the vulnerable plaque image in the preprocessed image by using a multi-task neural network. The classification is connected with the input end of the segmented vulnerable plaque image for region refinement subsystem.

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Abstract

The invention discloses a cardiovascular vulnerable plaque recognition method and system based on an attention model and a multi-task neural network. The method comprises the steps of (1) eliminatingnoise in an original polar coordinate image based on a top-down attention model, (2) classifying and segmenting a vulnerable plaque image in a preprocessed image by using a multi-task neural network,and (3) performing regional refinement on a classified and segmented vulnerable plaque image. The system includes a subsystem which eliminates the noise in the original polar coordinate image to obtain the preprocessed image based on the top-down attention model, a subsystem which classifies and segments a vulnerable plaque in the preprocessed image by using the multi-task neural network and a subsystem which carries out regional refinement on the classified and segmented vulnerable plaque image, and the subsystems are connected in order. The noise interference of a blood vessel to subsequentvulnerable plaque recognition is eliminated, and thus the positioning of the vulnerable plaque is more accurate.

Description

technical field [0001] The invention belongs to the field of medical image processing, and relates to a cardiovascular vulnerable plaque recognition method and system based on an attention model and a multi-task neural network. Background technique [0002] Vulnerable plaque is the most dangerous plaque in coronary atherosclerotic lesions. Vulnerable plaque is the main cause of thrombosis, acute coronary syndrome, and even sudden death. Therefore, detection and identification of various plaques Vulnerable plaque has a very high value. Cardiovascular optical coherence tomography is an intravascular imaging technology using near-infrared light reflection imaging, which can clearly observe vulnerable plaques. Therefore, the identification of vulnerable plaques based on optical coherence tomography (OCT) has become a important research trends. [0003] Commonly used performance evaluation criteria for OCT vulnerable plaques include: the recall rate R of vulnerable plaque detec...

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Application Information

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IPC IPC(8): G06T5/00G06T7/11G06K9/62
CPCG06T5/002G06T7/11G06T2207/20081G06T2207/20084G06T2207/20076G06T2207/10101G06T2207/30101G06T2207/30096G06F18/24
Inventor 辛景民白琼石培文刘思杰邓杨阳郑南宁
Owner XI AN JIAOTONG UNIV
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