图像理解与数据分析 |
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医学影像处理的深度学习可解释性研究进展 |
陈园琼1,2,3,4, 邹北骥1,3,4, 张美华2, 廖望旻1,3,4, 黄嘉儿1,3,4, 朱承璋3,4,5 |
1.中南大学 计算机学院,湖南 长沙 410083 2.吉首大学 软件学院,湖南 张家界 427000 3.移动医疗”教育部-中国移动联合实验室,湖南 长沙 410083 4.机器视觉与智慧医疗工程技术中心,湖南 长沙 410083 5.中南大学 文学与新闻传播学院,湖南 长沙 410083 |
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A review on deep learning interpretability in medical image processing |
CHEN Yuanqiong1,2,3,4, ZOU Beiji1,3,4, ZHANG Meihua2, LIAO Wangmin1,3,4, HUANG Jiaer1,3,4, ZHU Chengzhang3,4,5 |
1.School of Computer Science and Engineering, Central South University, Changsha 410083, China 2.Software College, Jishou University, Zhangjiajie 427000, Hunan Province, China 3.Mobile Health Ministry of Education-China Mobile Joint Laboratory, Changsha 410083, China 4.Hunan Engineering Research Center of Machine Vision and Intelligent Medicine, Central South University, Changsha 410083, China 5.The College of Literature and Journalism, Central South University, Changsha 410083, China |
引用本文:
陈园琼, 邹北骥, 张美华, 廖望旻, 黄嘉儿, 朱承璋. 医学影像处理的深度学习可解释性研究进展[J]. 浙江大学学报(理学版), 2021, 48(1): 18-29.
CHEN Yuanqiong, ZOU Beiji, ZHANG Meihua, LIAO Wangmin, HUANG Jiaer, ZHU Chengzhang. A review on deep learning interpretability in medical image processing. Journal of Zhejiang University (Science Edition), 2021, 48(1): 18-29.
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