Polyp Segmentation in NBI Colonoscopy

Author:

Gross Sebastian,Kennel Manuel,Stehle Thomas,Wulff Jonas,Tischendorf Jens,Trautwein Christian,Aach Til

Publisher

Springer Berlin Heidelberg

Reference9 articles.

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2. Tischendorf JJW, Wasmuth HE, Koch A, et al. Value of magnifying chromoendoscopy and narrow band imaging (NBI) in classifying colorectal polyps: A prospective controlled study. Endoscopy. 2007;39(12):1092–6.

3. Bourbakis N. Detecting abnormal patterns in WCE images. Procs IEEE BIBE. 2005; p. 232–238.

4. Kang J, Doraiswami R. Real-time image processing system for endoscopic applications. In: Canadian Conference on Electrical and Computer Engineering (IEEE CCECE). vol. 3; 2003. p. 1469–1472.

5. Hwang S, Oh J, Tavanapong W,et al. Polyp detection in colonoscopy video using elliptical shape feature. Procs ICIP. 2007;2:II–465–II–468.

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1. GastroSegNet: Polyp Segmentation using Colonoscopic Images Based on AttentionU-net Architecture;2023 10th International Conference on Wireless Networks and Mobile Communications (WINCOM);2023-10-26

2. DMAGNet: Dual‐path multi‐scale attention guided network for medical image segmentation;IET Image Processing;2023-08-09

3. AttResDU-Net: Medical Image Segmentation Using Attention-based Residual Double U-Net;2023 International Joint Conference on Neural Networks (IJCNN);2023-06-18

4. CRCNet: Global-local context and multi-modality cross attention for polyp segmentation;Biomedical Signal Processing and Control;2023-05

5. PolypSeg+: A Lightweight Context-Aware Network for Real-Time Polyp Segmentation;IEEE Transactions on Cybernetics;2023-04

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