Amita Shukla‐Dave

This paper introduces a cloud-based framework for AI medical image analysis using pyCERR and Cancer Genomics Cloud, enabling end-to-end workflows without local software installation.

This study examines how CT scan reconstruction kernels and tube current settings affect radiomic features, finding that some features are robust while others vary significantly.

STRATIS provides cloud-enabled software workflows for AI modeling in radiotherapy and imaging analysis, supporting multi-institutional collaboration and deployment.

The paper presents an open-source library of deep-learning models for image segmentation and outcomes in oncology, enabling validation, automation, and integration into clinical workflows.

This study introduces an optimal mass transport model to analyze contrast agent flow in head and neck cancer patients, showing comparable results to traditional methods.