10 citations · 11 across the 14 of their papers we have counts for
14 papers
iTRIALSPACE: Programmable Virtual Lesion Trials for Controlled Evaluation of Lung CT Models
Fakrul Islam Tushar, Umme Hafsa Momy, Joseph Y. Lo +1
We introduce iTRIALSPACE, a programmable evaluation framework for controlled assessment of lung CT models. Standard benchmarks are static retrospective collections that entangle le…
ORACLE-CT: Anatomy-Aware Support Pooling for CT Classification
Lavsen Dahal, Yubraj Bhandari, Geoffrey Rubin +1
Abdominal CT disease classification is challenging because each scan is a large 3D volume with many possible findings, while diagnostic evidence is often confined to specific organ…
JANUS: Anatomy-Conditioned Gating for Robust CT Triage Under Distribution Shift
Lavsen Dahal, Yubraj Bhandari, Geoffrey Rubin +1
Automated CT triage requires models that are simultaneously accurate across diverse pathologies and reliable under institutional shift. While Vision Transformers provide strong vis…
CT-IDP: Segmentation-Derived Quantitative Phenotypes for Interpretable Abdominal CT Disease Classification
Lavsen Dahal, Joseph Y. Lo
In this retrospective multi-institutional study, a quantitative phenotyping framework, CT-IDP (CT Image-Derived Phenotypes) was developed on the MERLIN abdominal CT benchmark (trai…
AbdomenGen: Sequential Volume-Conditioned Diffusion Framework for Abdominal Anatomy Generation
Yubraj Bhandari, Lavsen Dahal, Paul Segars +1
Computational phantoms are widely used in medical imaging research, yet current systems to generate controlled, clinically meaningful anatomical variations remain limited. We prese…
Tri-Reader: An Open-Access, Multi-Stage AI Pipeline for First-Pass Lung Nodule Annotation in Screening CT
Fakrul Islam Tushar, Joseph Y. Lo
Using multiple open-access models trained on public datasets, we developed Tri-Reader, a comprehensive, freely available pipeline that integrates lung segmentation, nodule detectio…
Organ-Aware Attention Improves CT Triage and Classification
Lavsen Dahal, Yubraj Bhandari, Geoffrey D. Rubin +1
There is an urgent need for triage and classification of high-volume medical imaging modalities such as computed tomography (CT), which can improve patient care and mitigate radiol…
NodMAISI: Nodule-Oriented Medical AI for Synthetic Imaging
Fakrul Islam Tushar, Ehsan Samei, Cynthia Rudin +1
Objective: Although medical imaging datasets are increasingly available, abnormal and annotation-intensive findings critical to lung cancer screening, particularly small pulmonary…
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…
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…
What limits performance of weakly supervised deep learning for chest CT classification?
Fakrul Islam Tushar, Vincent M. D'Anniballe, Geoffrey D. Rubin +1
Weakly supervised learning with noisy data has drawn attention in the medical imaging community due to the sparsity of high-quality disease labels. However, little is known about t…