10 citations · 13 across the 10 of their papers we have counts for
10 papers
Lymphocyte Mimicry Correction via Region-Level Tissue Reasoning and Unbalanced Optimal Transport
Xiang Li, Yuqi Wang, Casey C. Heirman +2
Cell mimicry arises when different cell types appear morphologically similar. Human pathologists resolve this ambiguity using surrounding tissue context, whereas current vision mod…
Demographic Distribution Matching between real world and virtual phantom population
Dhrubajyoti Ghosh, Fakrul Islam Tushar, Lavsen Dahal +5
Virtual imaging trials (VITs) offer scalable and cost-effective tools for evaluating imaging systems and protocols. However, their translational impact depends on rigorous comparab…
Zero-Shot Multi-Disease Labeling of Chest, Abdomen, and Pelvis CT Reports Using Open-Weight Large Language Models: The Effect of Labeling Conventions
Michael E. Garcia-Alcoser, Mobina Ghojoghnejad, Fakrul Islam Tushar +4
Purpose: To compare five lightweight open-weight large language models (LLMs) with a rule-based algorithm (RBA) and fine-tuned RadBERT for zero-shot labeling of chest-abdomen-pelvi…
Virtual Patients, Real Gains: Digital Twin-Based Simulated CT for Multitask Lung Nodule Analysis
Fakrul Islam Tushar, Lavsen Dahal, Paul Segars +1
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…
XCAT-3.0: A Comprehensive Library of Personalized Digital Twins Derived from CT Scans
Lavsen Dahal, Mobina Ghojoghnejad, Dhrubajyoti Ghosh +10
Virtual Imaging Trials (VIT) offer a cost-effective and scalable approach for evaluating medical imaging technologies. Computational phantoms, which mimic real patient anatomy and…
Reproducible Benchmarking for Lung Nodule Detection and Malignancy Classification Across Multiple Low-Dose CT Datasets
Fakrul Islam Tushar, Avivah Wang, Lavsen Dahal +7
Evaluation of artificial intelligence (AI) models for low-dose CT lung cancer screening is limited by heterogeneous datasets, annotation standards, and evaluation protocols, making…
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…
A personalized Uncertainty Quantification framework for patient survival models: estimating individual uncertainty of patients with metastatic brain tumors in the absence of ground truth
Yuqi Wang, Aarzu Gupta, David Carpenter +9
TodevelopanovelUncertaintyQuantification (UQ) framework to estimate the uncertainty of patient survival models in the absence of ground truth, we developed and evaluated our approa…
Large Intestine 3D Shape Refinement Using Point Diffusion Models for Digital Phantom Generation
Kaouther Mouheb, Mobina Ghojogh Nejad, Lavsen Dahal +4
Accurate 3D modeling of human organs is critical for constructing digital phantoms in virtual imaging trials. However, organs such as the large intestine remain particularly challe…
Duke Spleen Data Set: A Publicly Available Spleen MRI and CT dataset for Training Segmentation
Yuqi Wang, Jacob A. Macdonald, Katelyn R. Morgan +7
Spleen volumetry is primarily associated with patients suffering from chronic liver disease and portal hypertension, as they often have spleens with abnormal shapes and sizes. Howe…