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D. Jha, P. H. Smedsrud, D. Johansen, T. de Lange, H. D. Johansen, P. Halvorsen, and M. Riegler. "A Comprehensive Study on Colorectal Polyp Segmentation with ResUNet++, Conditional Random Field and Test-Time Augmentation." IEEE Journal of Biomedical and Health Informatics 25, no. 6 (2021): 2029-2040.PDF icon 09314114.pdf (6.16 MB)
N. KumarTomar, N. Ibtehaz, D. Jha, P. Halvorsen, and S. Ali. Improving generalizibilty in polyp segmentation using ensemble convolutional neural network In 3rd International Workshop and Challenge on Computer Vision in Endoscopy (EndoCV2021). Vol. 2886. CEUR Workshop Proceedings, 2021.
D. Jha, N. K. Tomar, S. Ali, M. Riegler, H. D. Johansen, D. Johansen, T. de Lange, and P. Halvorsen. NanoNet: Real-Time Polyp Segmentation in Video Capsule Endoscopy and Colonoscopy In 34th IEEE CBMS International Symposium on Computer-Based Medical Systems. IEEE, 2021.PDF icon 412100a037.pdf (789.29 KB)
G. Ji, Y. Chou, D. Fan, G. Chen, H. Fu, D. Jha, and L. Shao. Progressively Normalized Self-Attention Network for Video Polyp Segmentation In Medical Image Computing and Computer Assisted Intervention (MICCAI 2021). Vol. LNCS, volume 12901. Springer, 2021.
D. Jha, P. H. Smedsrud, M. Riegler, D. Johansen, T. de Lange, P. Halvorsen, and H. D. Johansen. ResUNet++: An Advanced Architecture for Medical Image Segmentation In 2019 IEEE International Symposium on Multimedia (ISM). San Diego, California, USA: IEEE, 2019.PDF icon resunet_accepted_debesh.pdf (1.01 MB)