1 code implementation • CVPR 2024 • Soumen Basu, Mayuna Gupta, Chetan Madan, Pankaj Gupta, Chetan Arora
We validate the proposed methods on the curated dataset, and report a new state-of-the-art (SOTA) accuracy of 96. 4% for the GBC detection problem, against an accuracy of 84% by current Image-based SOTA - GBCNet, and RadFormer, and 94. 7% by Video-based SOTA - AdaMAE.
no code implementations • 11 Sep 2023 • Soumen Basu, Ashish Papanai, Mayank Gupta, Pankaj Gupta, Chetan Arora
We posit that even when we have only the image level label, still formulating the problem as object detection (with bounding box output) helps a deep neural network (DNN) model focus on the relevant region of interest.
1 code implementation • 9 Nov 2022 • Soumen Basu, Mayank Gupta, Pratyaksha Rana, Pankaj Gupta, Chetan Arora
We propose a novel deep neural network architecture to learn interpretable representation for medical image analysis.
1 code implementation • 26 Jul 2022 • Soumen Basu, Somanshu Singla, Mayank Gupta, Pratyaksha Rana, Pankaj Gupta, Chetan Arora
We further validate the generalizability of our method on a publicly available lung US image dataset of COVID-19 pathologies and show an improvement of 1. 5% compared to SOTA.
1 code implementation • CVPR 2022 • Soumen Basu, Mayank Gupta, Pratyaksha Rana, Pankaj Gupta, Chetan Arora
However, USG images are challenging to analyze due to low image quality, noise, and varying viewpoints due to the handheld nature of the sensor.
Ranked #1 on Gallbladder Cancer Detection on GBCU