collaborators

5 papers

eess.IV2026

The Utility of the Virtual Imaging Trials Methodology for Objective Characterization of AI Systems and Training Data

Fakrul Islam Tushar, Lavsen Dahal, Saman Sotoudeh-Paima +4

Purpose: The credibility of Artificial Intelligence (AI) models for medical imaging continues to be a challenge, affected by the diversity of models, the data used to train the mod…

physics.med-ph2026

Proton therapy range uncertainty reduction using vendor-agnostic tissue characterization on a virtual photon-counting CT head scan

S. Vrbaški, G. Stanić, S. Molinelli +4

In this work, we proposed virtual imaging simulators as an alternative approach to experimental validation of beam range uncertainty in complex patient geometry using a computation…

cs.LG2025

Reinforcement Learning-Based Optimization of CT Acquisition and Reconstruction Parameters Through Virtual Imaging Trials

David Fenwick, Navid NaderiAlizadeh, Vahid Tarokh +7

Protocol optimization is critical in Computed Tomography (CT) to achieve high diagnostic image quality while minimizing radiation dose. However, due to the complex interdependencie…

cs.LG2025

Virtual Patients, Real Gains: Digital Twin-Based Simulated CT for Multitask Lung Nodule Analysis

Fakrul Islam Tushar, Lavsen Dahal, Cindy McCabe +6

AI-based lung cancer screening is constrained by scarce, annotated CT data, particularly for rare nodule presentations. We investigate whether physics-based, anatomy-informed simul…

eess.IV2025

Virtual Lung Screening Trial (VLST): An In Silico Study Inspired by the National Lung Screening Trial for Lung Cancer Detection

Fakrul Islam Tushar, Liesbeth Vancoillie, Cindy McCabe +16

Clinical imaging trials play a crucial role in advancing medical innovation but are often costly, inefficient, and ethically constrained. Virtual Imaging Trials (VITs) present a so…