155 related articles for article (PubMed ID: 34316372)
1. Automatic anatomical classification of colonoscopic images using deep convolutional neural networks.
Saito H; Tanimoto T; Ozawa T; Ishihara S; Fujishiro M; Shichijo S; Hirasawa D; Matsuda T; Endo Y; Tada T
Gastroenterol Rep (Oxf); 2021 Jun; 9(3):226-233. PubMed ID: 34316372
[TBL] [Abstract][Full Text] [Related]
2. Computer-Aided Diagnosis Based on Convolutional Neural Network System for Colorectal Polyp Classification: Preliminary Experience.
Komeda Y; Handa H; Watanabe T; Nomura T; Kitahashi M; Sakurai T; Okamoto A; Minami T; Kono M; Arizumi T; Takenaka M; Hagiwara S; Matsui S; Nishida N; Kashida H; Kudo M
Oncology; 2017; 93 Suppl 1():30-34. PubMed ID: 29258081
[TBL] [Abstract][Full Text] [Related]
3. Automatic anatomical classification of esophagogastroduodenoscopy images using deep convolutional neural networks.
Takiyama H; Ozawa T; Ishihara S; Fujishiro M; Shichijo S; Nomura S; Miura M; Tada T
Sci Rep; 2018 May; 8(1):7497. PubMed ID: 29760397
[TBL] [Abstract][Full Text] [Related]
4. Improved Accuracy in Optical Diagnosis of Colorectal Polyps Using Convolutional Neural Networks with Visual Explanations.
Jin EH; Lee D; Bae JH; Kang HY; Kwak MS; Seo JY; Yang JI; Yang SY; Lim SH; Yim JY; Lim JH; Chung GE; Chung SJ; Choi JM; Han YM; Kang SJ; Lee J; Chan Kim H; Kim JS
Gastroenterology; 2020 Jun; 158(8):2169-2179.e8. PubMed ID: 32119927
[TBL] [Abstract][Full Text] [Related]
5. Automated endoscopic detection and classification of colorectal polyps using convolutional neural networks.
Ozawa T; Ishihara S; Fujishiro M; Kumagai Y; Shichijo S; Tada T
Therap Adv Gastroenterol; 2020; 13():1756284820910659. PubMed ID: 32231710
[TBL] [Abstract][Full Text] [Related]
6. Density clustering-based automatic anatomical section recognition in colonoscopy video using deep learning.
Kim BS; Cho M; Chung GE; Lee J; Kang HY; Yoon D; Cho WS; Lee JC; Bae JH; Kong HJ; Kim S
Sci Rep; 2024 Jan; 14(1):872. PubMed ID: 38195632
[TBL] [Abstract][Full Text] [Related]
7. A novel machine learning-based algorithm to identify and classify lesions and anatomical landmarks in colonoscopy images.
Jheng YC; Wang YP; Lin HE; Sung KY; Chu YC; Wang HS; Jiang JK; Hou MC; Lee FY; Lu CL
Surg Endosc; 2022 Jan; 36(1):640-650. PubMed ID: 33591447
[TBL] [Abstract][Full Text] [Related]
8. Deep Learning Localizes and Identifies Polyps in Real Time With 96% Accuracy in Screening Colonoscopy.
Urban G; Tripathi P; Alkayali T; Mittal M; Jalali F; Karnes W; Baldi P
Gastroenterology; 2018 Oct; 155(4):1069-1078.e8. PubMed ID: 29928897
[TBL] [Abstract][Full Text] [Related]
9. Prediction of the histology of colorectal neoplasm in white light colonoscopic images using deep learning algorithms.
Choi SJ; Kim ES; Choi K
Sci Rep; 2021 Mar; 11(1):5311. PubMed ID: 33674628
[TBL] [Abstract][Full Text] [Related]
10. Novel computer-assisted diagnosis system for endoscopic disease activity in patients with ulcerative colitis.
Ozawa T; Ishihara S; Fujishiro M; Saito H; Kumagai Y; Shichijo S; Aoyama K; Tada T
Gastrointest Endosc; 2019 Feb; 89(2):416-421.e1. PubMed ID: 30367878
[TBL] [Abstract][Full Text] [Related]
11. Challenges Facing the Detection of Colonic Polyps: What Can Deep Learning Do?
Azer SA
Medicina (Kaunas); 2019 Aug; 55(8):. PubMed ID: 31409050
[TBL] [Abstract][Full Text] [Related]
12. Automatic detection and segmentation of adenomatous colorectal polyps during colonoscopy using Mask R-CNN.
Meng J; Xue L; Chang Y; Zhang J; Chang S; Liu K; Liu S; Wang B; Yang K
Open Life Sci; 2020; 15(1):588-596. PubMed ID: 33817247
[TBL] [Abstract][Full Text] [Related]
13. Accurate Classification of Diminutive Colorectal Polyps Using Computer-Aided Analysis.
Chen PJ; Lin MC; Lai MJ; Lin JC; Lu HH; Tseng VS
Gastroenterology; 2018 Feb; 154(3):568-575. PubMed ID: 29042219
[TBL] [Abstract][Full Text] [Related]
14. Automatic Polyp Segmentation in Colonoscopy Images Using a Modified Deep Convolutional Encoder-Decoder Architecture.
Eu CY; Tang TB; Lin CH; Lee LH; Lu CK
Sensors (Basel); 2021 Aug; 21(16):. PubMed ID: 34451072
[TBL] [Abstract][Full Text] [Related]
15. An automated detection system for colonoscopy images using a dual encoder-decoder model.
Hwang M; Wang D; Kong XX; Wang Z; Li J; Jiang WC; Hwang KS; Ding K
Comput Med Imaging Graph; 2020 Sep; 84():101763. PubMed ID: 32805673
[TBL] [Abstract][Full Text] [Related]
16. Lower Adenoma Miss Rate of Computer-Aided Detection-Assisted Colonoscopy vs Routine White-Light Colonoscopy in a Prospective Tandem Study.
Wang P; Liu P; Glissen Brown JR; Berzin TM; Zhou G; Lei S; Liu X; Li L; Xiao X
Gastroenterology; 2020 Oct; 159(4):1252-1261.e5. PubMed ID: 32562721
[TBL] [Abstract][Full Text] [Related]
17. Characterizing variability of in vivo Raman spectroscopic properties of different anatomical sites of normal colorectal tissue towards cancer diagnosis at colonoscopy.
Bergholt MS; Zheng W; Lin K; Wang J; Xu H; Ren JL; Ho KY; Teh M; Yeoh KG; Huang Z
Anal Chem; 2015 Jan; 87(2):960-6. PubMed ID: 25495077
[TBL] [Abstract][Full Text] [Related]
18. Application of artificial intelligence using a convolutional neural network for diagnosis of early gastric cancer based on magnifying endoscopy with narrow-band imaging.
Ueyama H; Kato Y; Akazawa Y; Yatagai N; Komori H; Takeda T; Matsumoto K; Ueda K; Matsumoto K; Hojo M; Yao T; Nagahara A; Tada T
J Gastroenterol Hepatol; 2021 Feb; 36(2):482-489. PubMed ID: 32681536
[TBL] [Abstract][Full Text] [Related]
19. Polyp detection during colonoscopy using a regression-based convolutional neural network with a tracker.
Zhang R; Zheng Y; Poon CCY; Shen D; Lau JYW
Pattern Recognit; 2018 Nov; 83():209-219. PubMed ID: 31105338
[TBL] [Abstract][Full Text] [Related]
20. Computer-Aided Diagonosis for Colorectal Cancer using Deep Learning with Visual Explanations.
Choi K; Choi SJ; Kim ES
Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():1156-1159. PubMed ID: 33018192
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
