2 citations · 6 across the 9 of their papers we have counts for
9 papers
Liver Cirrhosis Stage Estimation from MRI with Deep Learning
Jun Zeng, Debesh Jha, Ertugrul Aktas +8
We present an end-to-end deep learning framework for automated liver cirrhosis stage estimation from multi-sequence MRI. Cirrhosis is the severe scarring (fibrosis) of the liver an…
Large Scale MRI Collection and Segmentation of Cirrhotic Liver
Debesh Jha, Onkar Kishor Susladkar, Vandan Gorade +14
Liver cirrhosis represents the end stage of chronic liver disease, characterized by extensive fibrosis and nodular regeneration that significantly increases mortality risk. While m…
A Novel Momentum-Based Deep Learning Techniques for Medical Image Classification and Segmentation
Koushik Biswas, Ridal Pal, Shaswat Patel +10
Accurately segmenting different organs from medical images is a critical prerequisite for computer-assisted diagnosis and intervention planning. This study proposes a deep learning…
Towards Synergistic Deep Learning Models for Volumetric Cirrhotic Liver Segmentation in MRIs
Vandan Gorade, Onkar Susladkar, Gorkem Durak +7
Liver cirrhosis, a leading cause of global mortality, requires precise segmentation of ROIs for effective disease monitoring and treatment planning. Existing segmentation models of…
Ethical Framework for Responsible Foundational Models in Medical Imaging
Debesh Jha, Gorkem Durak, Abhijit Das +33
The emergence of foundational models represents a paradigm shift in medical imaging, offering extraordinary capabilities in disease detection, diagnosis, and treatment planning. Th…
MDNet: Multi-Decoder Network for Abdominal CT Organs Segmentation
Debesh Jha, Nikhil Kumar Tomar, Koushik Biswas +11
Accurate segmentation of organs from abdominal CT scans is essential for clinical applications such as diagnosis, treatment planning, and patient monitoring. To handle challenges o…
PAM-UNet: Shifting Attention on Region of Interest in Medical Images
Abhijit Das, Debesh Jha, Vandan Gorade +7
Computer-aided segmentation methods can assist medical personnel in improving diagnostic outcomes. While recent advancements like UNet and its variants have shown promise, they fac…
CT Liver Segmentation via PVT-based Encoding and Refined Decoding
Debesh Jha, Nikhil Kumar Tomar, Koushik Biswas +7
Accurate liver segmentation from CT scans is essential for effective diagnosis and treatment planning. Computer-aided diagnosis systems promise to improve the precision of liver di…
Adaptive Smooth Activation for Improved Disease Diagnosis and Organ Segmentation from Radiology Scans
Koushik Biswas, Debesh Jha, Nikhil Kumar Tomar +7
In this study, we propose a new activation function, called Adaptive Smooth Activation Unit (ASAU), tailored for optimized gradient propagation, thereby enhancing the proficiency o…