10 citations · 17 across the 15 of their papers we have counts for
16 papers
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…
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…
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…
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…
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…
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…
Uncertainty Estimation in Deep 2D Echocardiography Segmentation
Lavsen Dahal, Aayush Kafle, Bishesh Khanal
2D echocardiography is the most common imaging modality for cardiovascular diseases. The portability and relatively low-cost nature of Ultrasound (US) enable the US devices needed…
Automatic Cobb Angle Detection using Vertebra Detector and Vertebra Corners Regression
Bidur Khanal, Lavsen Dahal, Prashant Adhikari +1
Correct evaluation and treatment of Scoliosis require accurate estimation of spinal curvature. Current gold standard is to manually estimate Cobb Angles in spinal X-ray images whic…
DSNet: Automatic Dermoscopic Skin Lesion Segmentation
Md. Kamrul Hasan, Lavsen Dahal, Prasad N. Samarakoon +2
Automatic segmentation of skin lesion is considered a crucial step in Computer Aided Diagnosis (CAD) for melanoma diagnosis. Despite its significance, skin lesion segmentation rema…
Brain Tissue Segmentation Using NeuroNet With Different Pre-processing Techniques
Fakrul Islam Tushar, Basel Alyafi, Md. Kamrul Hasan +1
Automatic segmentation of brain Magnetic Resonance Imaging (MRI) images is one of the vital steps for quantitative analysis of brain for further inspection. In this paper, NeuroNet…