3 papers
cs.CV2026
Weakly Supervised Pathology-Informed Representation Learning for PET-Based Content Retrieval of Intra-Tumour Heterogeneity
Rajat Vashistha, Sandra Brosda, Lauren G. Aoude +8
We propose a weakly supervised 18FFDG PET representation-learning framework for content based medical image retrieval, using H&E derived information during training while preservin…
eess.IV2025
Stress-testing cross-cancer generalizability of 3D nnU-Net for PET-CT tumor segmentation: multi-cohort evaluation with novel oesophageal and lung cancer datasets
Soumen Ghosh, Christine Jestin Hannan, Rajat Vashistha +8
Robust generalization is essential for deploying deep learning based tumor segmentation in clinical PET-CT workflows, where anatomical sites, scanners, and patient populations vary…
cs.MA2025
The potential role of AI agents in transforming nuclear medicine research and cancer management in India
Rajat Vashistha, Arif Gulzar, Parveen Kundu +3
India faces a significant cancer burden, with an incidence-to-mortality ratio indicating that nearly three out of five individuals diagnosed with cancer succumb to the disease. Whi…