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Survival rates for colorectal cancer are higher when polyps are detected at an early stage and can be removed before they develop into malignant tumors.
A deep learning framework for quality assessment and restoration in video endoscopy
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A comparison of blood vessel features and local binary patterns for colorectal polyp classification
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A benchmark for endoluminal scene segmentation of colonoscopy images
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Adaptive specular reflection detection and inpainting in colonoscopy video frames
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Towards a computed-aided diagnosis system in colonoscopy: automatic polyp segmentation using convolution neural networks
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Girshick, R. (2015) · 2015
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Hinton, G., Vinyals, O., and Dean, J. (2015) · 2015
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Faster r-cnn: Towards real-time object detection with region proposal networks
Ren, S., He, K., Girshick, R., and Sun, J. (2015) · 2015
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Automated polyp detection in colonoscopy videos using shape and context information
Tajbakhsh, N., Gurudu, S. R., and Liang, J. (2015) · 2015
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Lesion detection of endoscopy images based on convolutional neural network features
Zhu, R., Zhang, R., and Xue, D. (2015) · 2015
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Exploring the clinical potential of an automatic colonic polyp detection method based on the creation of energy maps
Fernández-Esparrach, G., Bernal, J., López-Cerón, M., Córdova, H., Sánchez-Montes, C., Rodríguez de Miguel, C., and Sánchez, F. J. (2016) · 2016
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Deep residual learning for image recognition
He, K., Zhang, X., Ren, S., and Sun, J. (2016) · 2016
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Generative adversarial networks for specular highlight removal in endoscopic images
Funke, I., Bodenstedt, S., Riediger, C., Weitz, J., and Speidel, S. (2018) · 2018
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Li, Z. and Hoiem, D. (2018) · 2018
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An efficient approach for polyps detection in endoscopic videos based on faster r-cnn
Mo, X., Tao, K., Wang, Q., and Wang, G. (2018) · 2018
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Y-net: A deep convolutional neural network for polyp detection
Mohammed, A., Yildirim, S., Farup, I., Pedersen, M., and Hovde, Ø. (2018) · 2018
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Automatic colon polyp detection using region based deep cnn and post learning approaches
Shin, Y., Qadir, H. A., Aabakken, L., Bergsland, J., and Balasingham, I. (2018) · 2018
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Cancer statistics, 2018
Siegel, R. L., Miller, K. D., and Jemal, A. (2018) · 2018
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Development and validation of a deep-learning algorithm for the detection of polyps during colonoscopy
Wang, P., Xiao, X., Brown, J. R. G., Berzin, T. M., Tu, M., Xiong, F., Hu, X., Liu, P., Song, Y., Zhang, D., et al. (2018) · 2018
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Automatic polyp recognition in colonoscopy images using deep learning and two-stage pyramidal feature prediction
Jia, X., Mai, X., Cui, Y., Yuan, Y., Xing, X., Seo, H., Xing, L., and Meng, M. Q.-H. (2019) · 2019
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Ensemble of instance segmentation models for polyp segmentation in colonoscopy images
Kang, J. and Gwak, J. (2019) · 2019
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Collaborative learning of semi-supervised segmentation and classification for medical images
Zhou, Y., He, X., Huang, L., Liu, L., Zhu, F., Cui, S., and Shao, L. (2019) · 2019
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Kvasir-seg: A segmented polyp dataset
Jha, D., Smedsrud, P. H., Riegler, M. A., Halvorsen, P., de Lange, T., Johansen, D., and Johansen, H. D. (2020) · 2020
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