203 citations · 216 across the 8 of their papers we have counts for
12 papers
Semi-Supervised Semantic Segmentation of Cell Nuclei via Diffusion-based Large-Scale Pre-Training and Collaborative Learning
Zhuchen Shao, Sourya Sengupta, Hua Li +1
Automated semantic segmentation of cell nuclei in microscopic images is crucial for disease diagnosis and tissue microenvironment analysis. Nonetheless, this task presents challeng…
A Test Statistic Estimation-based Approach for Establishing Self-interpretable CNN-based Binary Classifiers
Sourya Sengupta, Mark A. Anastasio
Interpretability is highly desired for deep neural network-based classifiers, especially when addressing high-stake decisions in medical imaging. Commonly used post-hoc interpretab…
De-speckling of Optical Coherence Tomography Images Using Anscombe Transform and a Noisier2noise Model
Arka Saha, Sourya Sengupta
Optical Coherence Tomography (OCT) image denoising is a fundamental problem as OCT images suffer from multiplicative speckle noise, resulting in poor visibility of retinal layers.…
Uncertainty aware and explainable diagnosis of retinal disease
Amitojdeep Singh, Sourya Sengupta, Mohammed Abdul Rasheed +2
Deep learning methods for ophthalmic diagnosis have shown considerable success in tasks like segmentation and classification. However, their widespread application is limited due t…
BIDEAL: A Toolbox for Bicluster Analysis -- Generation, Visualization and Validation
Nishchal K. Verma, T. Sharma, S. Dixit +3
This paper introduces a novel toolbox named BIDEAL for the generation of biclusters, their analysis, visualization, and validation. The objective is to facilitate researchers to us…
Explainable deep learning models in medical image analysis
Amitojdeep Singh, Sourya Sengupta, Vasudevan Lakshminarayanan
Deep learning methods have been very effective for a variety of medical diagnostic tasks and has even beaten human experts on some of those. However, the black-box nature of the al…