140 related articles for article (PubMed ID: 38083589)
1. TransResU-Net: A Transformer based ResU-Net for Real-Time Colon Polyp Segmentation.
Tomar NK; Shergill A; Rieders B; Bagci U; Jha D
Annu Int Conf IEEE Eng Med Biol Soc; 2023 Jul; 2023():1-4. PubMed ID: 38083589
[TBL] [Abstract][Full Text] [Related]
2. M
Fu J; Lin S; Zhou P; Guo Y; Wang Y
Phys Med Biol; 2022 Oct; 67(20):. PubMed ID: 36113443
[TBL] [Abstract][Full Text] [Related]
3. Automatic Polyp Segmentation with Multiple Kernel Dilated Convolution Network.
Tomar NK; Srivastava A; Bagci U; Jha D
Proc IEEE Int Symp Comput Based Med Syst; 2022 Jul; 2022():317-322. PubMed ID: 36777398
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. MCSF-Net: a multi-scale channel spatial fusion network for real-time polyp segmentation.
Liu W; Li Z; Xia J; Li C
Phys Med Biol; 2023 Aug; 68(17):. PubMed ID: 37582393
[TBL] [Abstract][Full Text] [Related]
6. Deep learning to find colorectal polyps in colonoscopy: A systematic literature review.
Sánchez-Peralta LF; Bote-Curiel L; Picón A; Sánchez-Margallo FM; Pagador JB
Artif Intell Med; 2020 Aug; 108():101923. PubMed ID: 32972656
[TBL] [Abstract][Full Text] [Related]
7. Real-time automatic detection system increases colonoscopic polyp and adenoma detection rates: a prospective randomised controlled study.
Wang P; Berzin TM; Glissen Brown JR; Bharadwaj S; Becq A; Xiao X; Liu P; Li L; Song Y; Zhang D; Li Y; Xu G; Tu M; Liu X
Gut; 2019 Oct; 68(10):1813-1819. PubMed ID: 30814121
[TBL] [Abstract][Full Text] [Related]
8. Focus U-Net: A novel dual attention-gated CNN for polyp segmentation during colonoscopy.
Yeung M; Sala E; Schönlieb CB; Rundo L
Comput Biol Med; 2021 Oct; 137():104815. PubMed ID: 34507156
[TBL] [Abstract][Full Text] [Related]
9. Is artificial intelligence the final answer to missed polyps in colonoscopy?
Lui TKL; Leung WK
World J Gastroenterol; 2020 Sep; 26(35):5248-5255. PubMed ID: 32994685
[TBL] [Abstract][Full Text] [Related]
10. GAR-Net: Guided Attention Residual Network for Polyp Segmentation from Colonoscopy Video Frames.
Raymann J; Rajalakshmi R
Diagnostics (Basel); 2022 Dec; 13(1):. PubMed ID: 36611415
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. A Comprehensive Study on Colorectal Polyp Segmentation With ResUNet++, Conditional Random Field and Test-Time Augmentation.
Jha D; Smedsrud PH; Johansen D; de Lange T; Johansen HD; Halvorsen P; Riegler MA
IEEE J Biomed Health Inform; 2021 Jun; 25(6):2029-2040. PubMed ID: 33400658
[TBL] [Abstract][Full Text] [Related]
13. Computer-aided automated diminutive colonic polyp detection in colonoscopy by using deep machine learning system; first indigenous algorithm developed in India.
Mazumdar S; Sinha S; Jha S; Jagtap B
Indian J Gastroenterol; 2023 Apr; 42(2):226-232. PubMed ID: 37145230
[TBL] [Abstract][Full Text] [Related]
14. Deep learning in CT colonography: differentiating premalignant from benign colorectal polyps.
Wesp P; Grosu S; Graser A; Maurus S; Schulz C; Knösel T; Fabritius MP; Schachtner B; Yeh BM; Cyran CC; Ricke J; Kazmierczak PM; Ingrisch M
Eur Radiol; 2022 Jul; 32(7):4749-4759. PubMed ID: 35083528
[TBL] [Abstract][Full Text] [Related]
15. CIFG-Net: Cross-level information fusion and guidance network for Polyp Segmentation.
Li W; Huang Z; Li F; Zhao Y; Zhang H
Comput Biol Med; 2024 Feb; 169():107931. PubMed ID: 38181608
[TBL] [Abstract][Full Text] [Related]
16. An efficient real-time colonic polyp detection with YOLO algorithms trained by using negative samples and large datasets.
Pacal I; Karaman A; Karaboga D; Akay B; Basturk A; Nalbantoglu U; Coskun S
Comput Biol Med; 2022 Feb; 141():105031. PubMed ID: 34802713
[TBL] [Abstract][Full Text] [Related]
17. SR-AttNet: An Interpretable Stretch-Relax Attention based Deep Neural Network for Polyp Segmentation in Colonoscopy Images.
Alam MJ; Fattah SA
Comput Biol Med; 2023 Jun; 160():106945. PubMed ID: 37163966
[TBL] [Abstract][Full Text] [Related]
18. PolyEffNetV1: A CNN based colorectal polyp detection in colonoscopy images.
Sadagopan R; Ravi S; Adithya SV; Vivekanandhan S
Proc Inst Mech Eng H; 2023 Mar; 237(3):406-418. PubMed ID: 36683465
[TBL] [Abstract][Full Text] [Related]
19. Effect of a deep-learning computer-aided detection system on adenoma detection during colonoscopy (CADe-DB trial): a double-blind randomised study.
Wang P; Liu X; Berzin TM; Glissen Brown JR; Liu P; Zhou C; Lei L; Li L; Guo Z; Lei S; Xiong F; Wang H; Song Y; Pan Y; Zhou G
Lancet Gastroenterol Hepatol; 2020 Apr; 5(4):343-351. PubMed ID: 31981517
[TBL] [Abstract][Full Text] [Related]
20. HIGF-Net: Hierarchical information-guided fusion network for polyp segmentation based on transformer and convolution feature learning.
Wang J; Tian S; Yu L; Zhou Z; Wang F; Wang Y
Comput Biol Med; 2023 Jul; 161():107038. PubMed ID: 37230017
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
