Chirag Jagad

CALM-VLM improves confidence and reliability in brain MRI classification by calibrating vision-language models and enabling selective prediction.

This paper generates synthetic brain MRI data using a Diffusion Transformer to augment neuroimaging datasets and improve dementia classification.

The paper generates synthetic diffusion MRI maps using diffusion models and evaluates their realism and utility for improving AI classifiers.

This study evaluates parameter-efficient fine-tuning methods for vision transformers in neuroimaging, showing they outperform full fine-tuning and training from scratch with fewer parameters.

This study evaluates 2D and 3D diffusion models for generating synthetic DTI maps, finding 3D models perform better in downstream tasks like sex and dementia classification.

This study compares explainable AI models for Alzheimer's disease classification using MRI scans, evaluating interpretability methods and generalization across different populations.