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Multi-task temporal convolutional networks for joint recognition of surgical phases and steps in gastric bypass procedures.

S. Ramesh, D. Dall'Alba, C. Gonzalez, T. Yu, P. Mascagni, D. Mutter, J. Marescaux, P. Fiorini, and N. Padoy. Int. J. Comput. Assist. Radiol. Surg., 16 (7): 1111-1119 (2021)

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Bernd Mütter

Manfred Mutter

Claus Mütter

Andreas Mutter

Wolfgang Mutter

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Latent Graph Representations for Critical View of Safety Assessment.A. Murali, D. Alapatt, P. Mascagni, A. Vardazaryan, A. Garcia, N. Okamoto, D. Mutter, and N. Padoy. IEEE Trans. Medical Imaging, 43 (3): 1247-1258 (March 2024)Rendezvous: Attention mechanisms for the recognition of surgical action triplets in endoscopic videos.C. Nwoye, T. Yu, C. Gonzalez, B. Seeliger, P. Mascagni, D. Mutter, J. Marescaux, and N. Padoy. Medical Image Anal., (2022)Challenges in Multi-centric Generalization: Phase and Step Recognition in Roux-en-Y Gastric Bypass Surgery.J. Lavanchy, S. Ramesh, D. Dall'Alba, C. Gonzalez, P. Fiorini, B. Müller-Stich, P. Nett, J. Marescaux, D. Mutter, and N. Padoy. CoRR, (2023)Weakly Supervised Temporal Convolutional Networks for Fine-grained Surgical Activity Recognition.S. Ramesh, D. Dall'Alba, C. Gonzalez, T. Yu, P. Mascagni, D. Mutter, J. Marescaux, P. Fiorini, and N. Padoy. CoRR, (2023)Weakly Supervised Convolutional LSTM Approach for Tool Tracking in Laparoscopic Videos.C. Nwoye, D. Mutter, J. Marescaux, and N. Padoy. CoRR, (2018)Virtual Radiofrequency Ablation of Liver Tumors.C. Villard, L. Soler, N. Papier, V. Agnus, S. Thery, A. Gangi, D. Mutter, and J. Marescaux. IS4TH, volume 2673 of Lecture Notes in Computer Science, page 366-374. Springer, (2003)ST(OR)2: Spatio-Temporal Object Level Reasoning for Activity Recognition in the Operating Room.I. Hamoud, M. Jamal, V. Srivastav, D. Mutter, N. Padoy, and O. Mohareri. MIDL, volume 227 of Proceedings of Machine Learning Research, page 1254-1268. PMLR, (2023)Future-State Predicting LSTM for Early Surgery Type Recognition.S. Kannan, G. Yengera, D. Mutter, J. Marescaux, and N. Padoy. CoRR, (2018)Weakly supervised convolutional LSTM approach for tool tracking in laparoscopic videos.C. Nwoye, D. Mutter, J. Marescaux, and N. Padoy. Int. J. Comput. Assist. Radiol. Surg., 14 (6): 1059-1067 (2019)Preserving Privacy in Surgical Video Analysis Using Artificial Intelligence: A Deep Learning Classifier to Identify Out-of-Body Scenes in Endoscopic Videos.J. Lavanchy, A. Vardazaryan, P. Mascagni, A. Consortium, D. Mutter, and N. Padoy. CoRR, (2023)

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Disambiguation of "Mutter, Didier"

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Multi-task temporal convolutional networks for joint recognition of surgical phases and steps in gastric bypass procedures.

Please choose a person to relate this publication to

Bernd Mütter

Manfred Mutter

Claus Mütter

Andreas Mutter

Wolfgang Mutter

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Mutter, Didier"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Multi-task temporal convolutional networks for joint recognition of surgical phases and steps in gastric bypass procedures.

Please choose a person to relate this publication to

Bernd Mütter

Manfred Mutter

Claus Mütter

Andreas Mutter

Wolfgang Mutter

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
EndNote
APA
Chicago
DIN 1505
Harvard
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Multi-task temporal convolutional networks for joint recognition of surgical phases and steps in gastric bypass procedures.