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Towards a Computed-Aided Diagnosis System in Colonoscopy: Automatic Polyp Segmentation Using Convolution Neural Networks.

, , , , , , , , , , , and . JMRR, 3 (2): 1840002:1-1840002:13 (2018)

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Comparative Validation of Polyp Detection Methods in Video Colonoscopy: Results From the MICCAI 2015 Endoscopic Vision Challenge., , , , , , , , , and 14 other author(s). IEEE Trans. Med. Imaging, 36 (6): 1231-1249 (2017)Towards a Computed-Aided Diagnosis System in Colonoscopy: Automatic Polyp Segmentation Using Convolution Neural Networks., , , , , , , , , and 2 other author(s). JMRR, 3 (2): 1840002:1-1840002:13 (2018)Fully convolutional neural networks for polyp segmentation in colonoscopy., , , , , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 10134 of SPIE Proceedings, page 101340F. SPIE, (2017)Widening siamese architectures for stereo matching., , and . Pattern Recognition Letters, (2019)Bayesian constrained local models with depth data., , , and . ICIP, page 1654-1658. IEEE, (2016)Widening siamese architectures for stereo matching., , and . CoRR, (2017)Towards computer-assisted TTTS: Laser ablation detection for workflow segmentation from fetoscopic video., , , , , , and . Int. J. Comput. Assist. Radiol. Surg., 13 (10): 1661-1670 (2018)