18 citations · 55 across the 15 of their papers we have counts for
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UQMIA: An Open, Hands-On Tutorial on Uncertainty Quantification in Medical Imaging Analysis with Large Language Model-Based Assessment of Educational Content
Benyamin Gheiji, Danial Elyassirad, Mahsa Vatanparast +2
Uncertainty quantification (UQ) is increasingly recognized as an important component of reliable machine learning in medical imaging, yet practical resources connecting UQ theory,…
CONRep: Uncertainty-Aware Vision-Language Report Drafting Using Conformal Prediction
Danial Elyassirad, Benyamin Gheiji, Mahsa Vatanparast +5
Automated radiology report drafting (ARRD) using vision-language models (VLMs) has advanced rapidly, yet most systems lack explicit uncertainty estimates, limiting trust and safe c…
CONSeg: Voxelwise Glioma Conformal Segmentation
Danial Elyassirad, Benyamin Gheiji, Mahsa Vatanparast +2
Background and Purpose: Glioma segmentation is crucial for clinical decisions and treatment planning. Uncertainty quantification methods, including conformal prediction (CP), can e…
Comparative Analysis of 2D and 3D ResNet Architectures for IDH and MGMT Mutation Detection in Glioma Patients
Danial Elyassirad, Benyamin Gheiji, Mahsa Vatanparast +5
Gliomas are the most common cause of mortality among primary brain tumors. Molecular markers, including Isocitrate Dehydrogenase (IDH) and O[6]-methylguanine-DNA methyltransferase…
Analysis of the BraTS 2023 Intracranial Meningioma Segmentation Challenge
Dominic LaBella, Ujjwal Baid, Omaditya Khanna +119
We describe the design and results from the BraTS 2023 Intracranial Meningioma Segmentation Challenge. The BraTS Meningioma Challenge differed from prior BraTS Glioma challenges in…
RadRotator: 3D Rotation of Radiographs with Diffusion Models
Pouria Rouzrokh, Bardia Khosravi, Shahriar Faghani +4
Transforming two-dimensional (2D) images into three-dimensional (3D) volumes is a well-known yet challenging problem for the computer vision community. In the medical domain, a few…
Multitask Brain Tumor Inpainting with Diffusion Models: A Methodological Report
Pouria Rouzrokh, Bardia Khosravi, Shahriar Faghani +3
Despite the ever-increasing interest in applying deep learning (DL) models to medical imaging, the typical scarcity and imbalance of medical datasets can severely impact the perfor…