5 papers
FedDermaSeg: Federated Learning for Dermatological Image Segmentation
Anabik Pal, Ganesh Patidar, Bikash Santra
Skin cancer is a major global health concern, and early detection and accurate lesion delineation are important for effective diagnosis and treatment planning. Automated skin lesio…
Multimodal Knowledge Distillation for Gastric Adenocarcinoma Classification from Whole-Slide Images
Shrihari Dumbre, Bikash Santra
Gastric adenocarcinoma (GA) is a leading cause of cancer-related mortality worldwide, and accurate histopathological subtype classification from whole-slide images (WSIs) is essent…
OptiModNet: A UNet-Transformer Hybrid with Grouped-Query and Channel Attention for Optic Disc and Cup Segmentation
Soumili Ghosh, Debapriya Roy, Aryan Das +1
Precise segmentation of the optic disc and cup is critical for the early detection and diagnosis of glaucoma. However, achieving consistently high performance across datasets while…
PRISMA: Preference-Reinforced Self-Training Approach for Interpretable Emotionally Intelligent Negotiation Dialogues
Prajwal Vijay Kajare, Priyanshu Priya, Bikash Santra +1
Emotion plays a pivotal role in shaping negotiation outcomes, influencing trust, cooperation, and long-term relationships. Developing negotiation dialog systems that can recognize…
A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT
Tanjin Taher Toma, Tejas Sudharshan Mathai, Bikash Santra +11
Accurate segmentation of pheochromocytoma (PCC) in abdominal CT scans is essential for tumor burden estimation, prognosis, and treatment planning. It may also help infer genetic cl…