1 code implementation • 18 Feb 2024 • Gautam Machiraju, Alexander Derry, Arjun Desai, Neel Guha, Amir-Hossein Karimi, James Zou, Russ Altman, Christopher Ré, Parag Mallick
Feature attribution, the ability to localize regions of the input data that are relevant for classification, is an important capability for machine learning models in scientific and biomedical domains.
1 code implementation • 13 Feb 2023 • Louis Blankemeier, Arjun Desai, Juan Manuel Zambrano Chaves, Andrew Wentland, Sally Yao, Eduardo Reis, Malte Jensen, Bhanushree Bahl, Khushboo Arora, Bhavik N. Patel, Leon Lenchik, Marc Willis, Robert D. Boutin, Akshay S. Chaudhari
Extracting quantitative body composition measures manually from CT scans is a cumbersome and time-consuming task.
1 code implementation • 13 Feb 2023 • Francesco Santini, Jakob Wasserthal, Abramo Agosti, Xeni Deligianni, Kevin R. Keene, Hermien E. Kan, Stefan Sommer, Christoph Stuprich, Fengdan Wang, Claudia Weidensteiner, Giulia Manco, Matteo Paoletti, Valentina Mazzoli, Arjun Desai, Anna Pichiecchio
Semantic segmentation is a crucial step to extract quantitative information from medical (and, specifically, radiological) images to aid the diagnostic process, clinical follow-up.
no code implementations • 17 Oct 2022 • Dave Van Veen, Rogier van der Sluijs, Batu Ozturkler, Arjun Desai, Christian Bluethgen, Robert D. Boutin, Marc H. Willis, Gordon Wetzstein, David Lindell, Shreyas Vasanawala, John Pauly, Akshay S. Chaudhari
We propose using a coordinate network decoder for the task of super-resolution in MRI.
1 code implementation • 1 Apr 2022 • Tri Dao, Beidi Chen, Nimit Sohoni, Arjun Desai, Michael Poli, Jessica Grogan, Alexander Liu, Aniruddh Rao, Atri Rudra, Christopher Ré
To address these issues, we propose a class of matrices (Monarch) that is hardware-efficient (they are parameterized as products of two block-diagonal matrices for better hardware utilization) and expressive (they can represent many commonly used transforms).
no code implementations • 13 Dec 2020 • Michael Zhang, Xiaotian Cheng, Daniel Copeland, Arjun Desai, Melody Y. Guan, Gabriel A. Brat, Serena Yeung
A state-of-the-art convolutional neural network architecture for object detection was used to detect operating hands in open surgery videos.