Search Results for author: Nithya Bhasker

Found 2 papers, 1 papers with code

Graph data modelling for outcome prediction in oropharyngeal cancer patients

no code implementations • 4 Oct 2023 • Nithya Bhasker, Stefan Leger, Alexander Zwanenburg, Chethan Babu Reddy, Sebastian Bodenstedt, Steffen Löck, Stefanie Speidel

Graph neural networks (GNNs) are becoming increasingly popular in the medical domain for the tasks of disease classification and outcome prediction.

Computed Tomography (CT) Inductive Learning

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CholecTriplet2021: A benchmark challenge for surgical action triplet recognition

6 code implementations • 10 Apr 2022 • Chinedu Innocent Nwoye, Deepak Alapatt, Tong Yu, Armine Vardazaryan, Fangfang Xia, Zixuan Zhao, Tong Xia, Fucang Jia, Yuxuan Yang, Hao Wang, Derong Yu, Guoyan Zheng, Xiaotian Duan, Neil Getty, Ricardo Sanchez-Matilla, Maria Robu, Li Zhang, Huabin Chen, Jiacheng Wang, Liansheng Wang, Bokai Zhang, Beerend Gerats, Sista Raviteja, Rachana Sathish, Rong Tao, Satoshi Kondo, Winnie Pang, Hongliang Ren, Julian Ronald Abbing, Mohammad Hasan Sarhan, Sebastian Bodenstedt, Nithya Bhasker, Bruno Oliveira, Helena R. Torres, Li Ling, Finn Gaida, Tobias Czempiel, João L. Vilaça, Pedro Morais, Jaime Fonseca, Ruby Mae Egging, Inge Nicole Wijma, Chen Qian, GuiBin Bian, Zhen Li, Velmurugan Balasubramanian, Debdoot Sheet, Imanol Luengo, Yuanbo Zhu, Shuai Ding, Jakob-Anton Aschenbrenner, Nicolas Elini van der Kar, Mengya Xu, Mobarakol Islam, Lalithkumar Seenivasan, Alexander Jenke, Danail Stoyanov, Didier Mutter, Pietro Mascagni, Barbara Seeliger, Cristians Gonzalez, Nicolas Padoy

In this paper, we present the challenge setup and assessment of the state-of-the-art deep learning methods proposed by the participants during the challenge.

Ranked #1 on Action Triplet Recognition on CholecT50 (Challenge) (using extra training data)

Action Detection Action Triplet Recognition +2

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