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Left ventricle segmentation method, system and device based on multi-feature fusion and medium
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A multi-feature fusion, left ventricular technology, applied in the field of medical image processing, can solve the problems of missing boundaries and lack of visual aids for radiologists, and achieve the effect of good diversity and good ensemble learning performance.
Active Publication Date: 2019-08-23
SHANDONG NORMAL UNIV
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Although it can assist radiologists in detailed quantitative analysis such as cardiac ejection fractionestimation, volume estimation, and quantification of the whole left ventricle, the absence of borders leaves radiologists without a visual aid
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Embodiment 1
[0033] Embodiment 1, this embodiment provides a left ventricle segmentation method based on multi-feature fusion;
[0034] Such as figure 1 As shown, the left ventricle segmentation method based on multi-feature fusion includes:
[0035] S1: Input the cardiac MRI image to be segmented;
[0036] S2: Input the cardiac MRI image to be segmented into the pre-trained left ventricle segmentation model based on multi-feature fusion, and output the left ventricle segmentation result.
[0037] Such as image 3 Said, as one or more embodiments, the left ventricle segmentation model based on multi-feature fusion includes:
[0038] The parallel first feature extraction module, the second feature extraction module and the third feature extraction module;
[0039] Perform feature fusion on the output values of the first feature extraction module, the second feature extraction module and the third feature extraction module, and input the fused features into the convolution layer to obt...
Embodiment 2
[0075] Embodiment 2, this embodiment also provides a left ventricle segmentation system based on multi-feature fusion;
[0076] Left ventricle segmentation system based on multi-feature fusion, including:
[0078] The segmentation module is configured to input the cardiac MRI image to be segmented into a pre-trained left ventricle segmentation model based on multi-feature fusion, and output a left ventricle segmentation result.
Embodiment 3
[0079] Embodiment 3. This embodiment also provides an electronic device, including a memory, a processor, and computer instructions stored in the memory and run on the processor. When the computer instructions are executed by the processor, each step in the method is completed. For the sake of brevity, the operation will not be repeated here.
[0080] Described electronic device can be mobile terminal and non-mobile terminal, and non-mobile terminal comprises desktop computer, and mobile terminal comprises smart phone (Smart Phone, such as Android mobile phone, IOS mobile phone etc.), smart glasses, smart watch, smart bracelet, tablet computer , laptops, personal digital assistants and other mobile Internet devices that can communicate wirelessly.
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Abstract
The invention discloses a left ventricle segmentation method, system and device based on multi-feature fusion and a medium. The method comprises: inputting a heart nuclear magnetic resonance image tobe segmented; and inputting the heart nuclear magnetic resonance image to be segmented into a pre-trained left ventricle segmentation model based on multi-feature fusion, and outputting a left ventricle segmentation result. A left ventricle segmentation model based on multi-feature fusion comprises a first feature extraction module, a second feature extraction module and a third feature extractionmodule which are arranged in parallel. Feature fusion is carried out on the output values of the first feature extraction module, the second feature extraction module and the third feature extractionmodule, and the fused features are input into a convolutional layer to obtain a segmentation result.
Description
technical field [0001] The present disclosure relates to the technical field of medical image processing, in particular to a left ventricle segmentation method, system, device and medium based on multi-feature fusion. Background technique [0002] The statements in this section merely mention background art related to the present disclosure and do not necessarily constitute prior art. [0003] In the process of realizing the present disclosure, the inventors found that the following technical problems existed in the prior art: [0004] Existing LV evaluation methods include: (1) LV segmentation methods and (2) LV quantification methods. [0005] (1) Left ventricle segmentation method. The borders of the myocardium can serve as a visual aid for radiologists. Although accurate myocardial segmentation can lead to detailed quantitative analysis, left ventricle quantification results require additional calculations, thus causing unnecessary errors and extra work. For example,...
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