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,Guang-Wei 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:93
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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