医学诊断
卷积神经网络
医学
金标准(测试)
淋巴结
放射科
接收机工作特性
淋巴
计算机科学
人工智能
病理
内科学
作者
Yun Lu,Qiyue Yu,Yuanxiang Gao,Yunpeng Zhou,Guangwei Liu,Qian Dong,Jinlong Ma,Lei Ding,Hongwei Yao,Zhongtao Zhang,Gang Xiao,Qi An,Guiying Wang,Jinchuan Xi,Weitang Yuan,Yugui Lian,Dianliang Zhang,Chunbo Zhao,Qin Yao,Wei Liu
出处
期刊:Cancer Research
[American Association for Cancer Research]
日期:2018-07-19
卷期号:78 (17): 5135-5143
被引量:98
标识
DOI:10.1158/0008-5472.can-18-0494
摘要
MRI is the gold standard for confirming a pelvic lymph node metastasis diagnosis. Traditionally, medical radiologists have analyzed MRI image features of regional lymph nodes to make diagnostic decisions based on their subjective experience; this diagnosis lacks objectivity and accuracy. This study trained a faster region-based convolutional neural network (Faster R-CNN) with 28,080 MRI images of lymph node metastasis, allowing the Faster R-CNN to read those images and to make diagnoses. For clinical verification, 414 cases of rectal cancer at various medical centers were collected, and Faster R-CNN-based diagnoses were compared with radiologist diagnoses using receiver operating characteristic curves (ROC). The area under the Faster R-CNN ROC was 0.912, indicating a more effective and objective diagnosis. The Faster R-CNN diagnosis time was 20 s/case, which was much shorter than the average time (600 s/case) of the radiologist diagnoses.Significance: Faster R-CNN enables accurate and efficient diagnosis of lymph node metastases. Cancer Res; 78(17); 5135-43. ©2018 AACR.
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