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Automatic Detection of Aortic Dissection Based on Morphology and Deep Learning 被引量:8

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摘要 Aortic dissection(AD)is a kind of acute and rapidly progressing cardiovascular disease.In this work,we build a CTA image library with 88 CT cases,43 cases of aortic dissection and 45 cases of health.An aortic dissection detection method based on CTA images is proposed.ROI is extracted based on binarization and morphology opening operation.The deep learning networks(InceptionV3,ResNet50,and DenseNet)are applied after the preprocessing of the datasets.Recall,F1-score,Matthews correlation coefficient(MCC)and other performance indexes are investigated.It is shown that the deep learning methods have much better performance than the traditional method.And among those deep learning methods,DenseNet121 can exceed other networks such as ResNet50 and InceptionV3.
出处 《Computers, Materials & Continua》 SCIE EI 2020年第3期1201-1215,共15页 计算机、材料和连续体(英文)
基金 This work is supported by the National Natural Science Foundation of China(No.61772561) the National Natural Science Foundation of Hunan(No.2019JJ50866) the Key Research&Development Plan of Hunan Province(No.2018NK2012) the Postgraduate Science and Technology Innovation Foundation of Central South University of Forestry and Technology(No.20183034).
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