output
20112025
most citedDeep Learning How to Fit an Intravoxel Incoherent Motion Model to Diffusion-Weighted MRI

145 citations

11 papers

cs.CV2025

A weakly-supervised deep learning model for fast localisation and delineation of the skeleton, internal organs, and spinal canal on Whole-Body Diffusion-Weighted MRI (WB-DWI)

A. Candito, A. Dragan, R. Holbrey +6

Background: Apparent Diffusion Coefficient (ADC) values and Total Diffusion Volume (TDV) from Whole-body diffusion-weighted MRI (WB-DWI) are recognized cancer imaging biomarkers. H…

q-bio.GN2025

Combining multiplexed functional data to improve variant classification

Atlas of Variant Effects Alliance, :, Jeffrey D. Calhoun +10

With the surge in the number of variants of uncertain significance (VUS) reported in ClinVar in recent years, there is an imperative to resolve VUS at scale. Multiplexed assays of…

physics.med-ph2024★ 5 cited

In vivo exposure of the bladder using a non-invasive high intensity focused ultrasound toroidal transducer

Victor Delattre, Sophie Cambronero, Yao Chen +5

A toroidal high-intensity focused ultrasound (HIFU) transducer was used to expose normal bladder wall tissues non-invasively in vivo in a porcine model in order to investigate the…

stat.AP2024★ 3 cited

A Bayesian hierarchical mixture cure modelling framework to utilize multiple survival datasets for long-term survivorship estimates: A case study from previously untreated metastatic melanoma

Nathan Green, Murat Kurt, Andriy Moshyk +2

Time to an event of interest over a lifetime is a central measure of the clinical benefit of an intervention used in a health technology assessment (HTA). Within the same trial, mu…

cs.CV2021★ 2 cited

Multiple Instance Learning with Auxiliary Task Weighting for Multiple Myeloma Classification

Talha Qaiser, Stefan Winzeck, Theodore Barfoot +9

Whole body magnetic resonance imaging (WB-MRI) is the recommended modality for diagnosis of multiple myeloma (MM). WB-MRI is used to detect sites of disease across the entire skele…

cs.CV2021

Learning from Partially Overlapping Labels: Image Segmentation under Annotation Shift

Gregory Filbrandt, Konstantinos Kamnitsas, David Bernstein +2

Scarcity of high quality annotated images remains a limiting factor for training accurate image segmentation models. While more and more annotated datasets become publicly availabl…