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Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge.

S. Ali, N. Ghatwary, D. Jha, E. Isik-Polat, G. Polat, C. Yang, W. Li, A. Galdran, M. Ballester, V. Thambawita, S. Hicks, S. Poudel, S. Lee, Z. Jin, T. Gan, C. Yu, J. Yan, D. Yeo, H. Lee, N. Tomar, M. Haithami, A. Ahmed, M. Riegler, C. Daul, P. Halvorsen, J. Rittscher, O. Salem, D. Lamarque, R. Cannizzaro, S. Realdon, T. de Lange, and J. East. CoRR, (2022)

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Jens Rittscher

Hauke Rittscher

Martin Rittscher

Hans Helge Jensen

Gerd Jensen

Other publications of authors with the same name

Highly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissue.M. Gerdes, C. Sevinsky, A. Sood, S. Adak, M. Bello, A. Bordwell, A. Can, A. Corwin, S. Dinn, R. Filkins and 21 other author(s). Proc. Natl. Acad. Sci. USA, 110 (29): 11982-11987 (2013)Capturing variations in nuclear phenotypes.S. Raman, S. Singh, T. Pécot, E. Caserta, K. Huang, J. Rittscher, G. Leone, and R. Machiraju. J. Comput. Sci., (2019)Endoscopy artifact detection (EAD 2019) challenge dataset.S. Ali, F. Zhou, C. Daul, B. Braden, A. Bailey, S. Realdon, J. East, G. Wagnières, V. Loschenov, E. Grisan and 2 other author(s). CoRR, (2019)Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy.S. Ali, M. Dmitrieva, N. Ghatwary, S. Bano, G. Polat, A. Temizel, A. Krenzer, A. Hekalo, Y. Guo, B. Matuszewski and 27 other author(s). Medical Image Anal., (2021)Self-Supervised Voxel-Level Representation Rediscovers Subcellular Structures in Volume Electron Microscopy.H. Han, M. Dmitrieva, A. Sauer, K. Tam, and J. Rittscher. CVPR Workshops, page 1873-1882. IEEE, (2022)MI-UNet: Improved Segmentation in Ureteroscopy.S. Gupta, S. Ali, L. Goldsmith, B. Turney, and J. Rittscher. ISBI, page 212-216. IEEE, (2020)Fine-Grained Multi-Instance Classification in Microscopy Through Deep Attention.M. Fan, T. Chakraborti, E. Chang, Y. Xu, and J. Rittscher. ISBI, page 169-173. IEEE, (2020)Towards the Identification of Histology Based Subtypes in Prostate Cancer.A. Chatrian, K. Sirinukunwattana, C. Verrill, and J. Rittscher. ISBI, page 948-952. IEEE, (2019)Motion induced segmentation of stone fragments in ureteroscopy video.S. Gupta, S. Ali, L. Goldsmith, B. Turney, and J. Rittscher. Medical Imaging: Image-Guided Procedures, volume 11315 of SPIE Proceedings, page 1131514. SPIE, (2020)Identification of C. elegans Strains Using a Fully Convolutional Neural Network on Behavioural Dynamics.A. Javer, A. Brown, I. Kokkinos, and J. Rittscher. ECCV Workshops (6), volume 11134 of Lecture Notes in Computer Science, page 455-464. Springer, (2018)

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Disambiguation of "Rittscher, Jens"

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Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge.

Please choose a person to relate this publication to

Jens Rittscher

Hauke Rittscher

Martin Rittscher

Hans Helge Jensen

Gerd Jensen

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Rittscher, Jens"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge.

Please choose a person to relate this publication to

Jens Rittscher

Hauke Rittscher

Martin Rittscher

Hans Helge Jensen

Gerd Jensen

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
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APA
Chicago
DIN 1505
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Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge.