Detection of early gastric cancer in white light imagings based on region-based convolutional neural networks

Jing Jin; Qianqian Zhang; Bill Dong; Tao Ma; Xi Wang; Xuecan Mei; Shaofang Song; Jie Peng; Aijiu Wu; Lanfang Dong; Derun Kong

Return

Detection of early gastric cancer in white light imagings based on region-based convolutional neural networks

Author: Jing Jin ^{1
,

2} ; Qianqian Zhang ^{1
,

2} ; Bill Dong ³ ; Tao Ma ³ ; Xi Wang ^{1
,

2} ; Xuecan Mei ^{1
,

2} ; Shaofang Song ⁴ ; Jie Peng ⁴ ; Aijiu Wu ⁴ ; Lanfang Dong ³ ; Derun Kong ^{1
,

2}
Author Information

1. Dept of Gastroenterology，The First Affiliated Hospital of Anhui Medical University，Hefei 230022
2. Key Laboratory of Digestive Diseases of Anhui Province，Hefei 230022
3. School of Computer Science and Technology，High-tech Campus，University of Science and Technology of China，Hefei 230027
4. Hefei Zhongna Medical Instrument Co．，Ltd，Hefei 230088
Publication Type:Journal Article
Keywords: artificial intelligence; region-based convolutional neural network; endoscopy; early gastric cancer
From: Acta Universitatis Medicinalis Anhui 2023;58(2):285-291
CountryChina
Language:Chinese
Abstract: Objective :To develop an endoscopic automatic detection system in early gastric cancer (EGC) based on a region-based convolutional neural network ( Mask R-CNN) ．
Methods : A total of 3 579 and 892 white light images (WLI) of EGC were obtained from the First Affiliated Hospital of Anhui Medical University for training and testing，respectively．Then，10 WLI videos were obtained prospectively to test dynamic performance of the RCNN system．In addition，400 WLI images were randomly selected for comparison with the Mask R-CNN system and endoscopists．Diagnostic ability was assessed by accuracy，sensitivity，specificity，positive predictive value ( PPV) ， and negative predictive value (NPV) .
Results : The accuracy，sensitivity and specificity of the Mask R-CNN system in diagnosing EGC in WLI images were 90. 25% ，91. 06% and 89. 01% ，respectively，and there was no significant statistical difference with the results of pathological diagnosis．Among WLI real-time videos，the diagnostic accuracy was 90. 27%．The speed of test videos was up to 35 frames / s in real time．In the controlled experiment， the sensitivity of Maks R-CNN system was higher than that of the experts (93. 00% vs 80. 20% ，χ2 = 7. 059，P < 0. 001) ，and the specificity was higher than that of the juniors (82. 67% vs 71. 87% ，χ2 = 9. 955，P＜0. 001) ， and the overall accuracy rate was higher than that of the seniors (85. 25% vs 78. 00% ，χ2 = 7. 009，P＜0. 001) .
Conclusion:The Mask R-CNN system has excellent performance for detection of EGC under WLI，which has great potential for practical clinical application.
Full text:2024071422335000054基于卷积神经网络的白光内镜下早期胃癌检测_晋晶.pdf