Yun Tan1, #, Ling Tan2, #, Xuyu Xiang1, *, Hao Tang2, *, Jiaohua Qin1, Wenyan Pan1
CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1201-1215, 2020, DOI:10.32604/cmc.2020.07127
Abstract 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 More >
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