4 papers · 1 filter
OTCXR: Rethinking Self-supervised Alignment using Optimal Transport for Chest X-ray Analysis
Vandan Gorade, Azad Singh, Deepak Mishra
Self-supervised learning (SSL) has emerged as a promising technique for analyzing medical modalities such as X-rays due to its ability to learn without annotations. However, conven…
L2GNet: Optimal Local-to-Global Representation of Anatomical Structures for Generalized Medical Image Segmentation
Vandan Gorade, Sparsh Mittal, Neethi Dasu +3
Continuous Latent Space (CLS) and Discrete Latent Space (DLS) models, like AttnUNet and VQUNet, have excelled in medical image segmentation. In contrast, Synergistic Continuous and…
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…
Rethinking Intermediate Layers design in Knowledge Distillation for Kidney and Liver Tumor Segmentation
Vandan Gorade, Sparsh Mittal, Debesh Jha +1
Knowledge distillation (KD) has demonstrated remarkable success across various domains, but its application to medical imaging tasks, such as kidney and liver tumor segmentation, h…