一种融合二维和三维卷积网络的两阶段冠状动脉分 割方法
一种融合二维和三维卷积网络的两阶段冠状动脉分 割方法
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国家科技部战略性科技创新合作项目(2021YFE0204300);国家自然科学基金面上项目(81871447);深圳湾实验室开放基金项目(SZBL2019062801002);深圳市科技创新委员会多方合作项目(JCYJ20180507182506416)

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A Two-Stage Coronary Artery Segmentation Method Based on the Combination of 2D and 3D Convolutional Neural Networks
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Strategic Science and Technology Innovation Cooperation Project of the Ministry of Science and Technology of China (2021YFE0204300), National Natural Science Foundation of China (81871447), Shenzhen Bay Laboratory Open Fund Project (SZBL2019062801002), and Shenzhen Science and Technology Innovation Commission (JCYJ20180507182506416)

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    摘要:

    心血管疾病是一种严重危害公众健康的重大疾病。与其他心血管疾病相比,冠心病是导致死亡的最主要原因,精确的冠状动脉分割对冠心病的治疗有重要意义。目前,深度学习已经广泛应用于医学影像领域,然而,像冠状动脉这样的小物体的分割仍然是一大挑战。针对冠状动脉精确分割的需求,该研究提出了一种融合二维和三维卷积网络的方案,利用骨架作为桥梁,结合二维和三维卷积网络,扩大了卷积网络的信息接受域。与其他深度学习方法相比,该方法在敏感度、Dice 系数、ROC 曲线下方的面积、豪斯多夫距离上均有一定程度的提升,且可以检测其他方法无法识别的冠状动脉,一定程度上解决了血管断连和血管缺失等问题。

    Abstract:

    Cardiovascular disease is a major disease that seriously endangers public health. Coronary heart disease is the leading cause of death compared with other cardiovascular diseases. Precise coronary artery segmentation is of great significance to the treatment of coronary heart disease. Deep learning has been widely used in the field of medical imaging, but the segmentation of small object like coronary arteries is still a challenge. Aiming at accurate coronary artery segmentation this research proposes a combination of 2D and 3D convolutional neural networks. Specifically, the proposed scheme uses skeleton as a bridge to combine the two kinds of convolution networks, and expand the information receiving domain of convolution network. Compared with other deep learning based methods, the proposed method exhibits a certain improvement in sensitivity, Dice coefficient, AUC, and Hausdorf distance, and can detect the coronary arteries that cannot be identified by other competing methods, which solves the problem of vascular disconnection and blood missing to a certain extent.

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引文格式
曾雨鸿,宋佳宁,刘嘉.一种融合二维和三维卷积网络的两阶段冠状动脉分 割方法 [J].集成技术,2022,11(3):98-107

Citing format
ZENG Yuhong, SONG Jianing, LIU Jia. A Two-Stage Coronary Artery Segmentation Method Based on the Combination of 2D and 3D Convolutional Neural Networks[J]. Journal of Integration Technology,2022,11(3):98-107

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  • 在线发布日期: 2022-05-18
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