output
20172025
most citedMultimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology

78 citations

11 papers

physics.med-ph2025

Real-time 3D Ultrasonic Needle Tracking with a Photoacoustic Beacon

Christian Baker, Weidong Liang, Richard Colchester +7

Many minimally invasive procedures, such as core needle biopsy of focal liver lesions, nerve blocks, and fetal and vascular interventions, are typically performed under ultrasound…

eess.IV2025★ 1 cited

KEVS: Enhancing Segmentation of Visceral Adipose Tissue in Pre-Cystectomy CT with Gaussian Kernel Density Estimation

Thomas Boucher, Nicholas Tetlow, Annie Fung +5

Purpose: The distribution of visceral adipose tissue (VAT) in cystectomy patients is indicative of the incidence of post-operative complications. Existing VAT segmentation methods…

cs.CV2024★ 14 cited

Machine learning algorithms to predict the risk of rupture of intracranial aneurysms: a systematic review

Karan Daga, Siddharth Agarwal, Zaeem Moti +5

Purpose: Subarachnoid haemorrhage is a potentially fatal consequence of intracranial aneurysm rupture, however, it is difficult to predict if aneurysms will rupture. Prophylactic t…

physics.med-ph2024★ 5 cited

Jump stochastic differential equations for the characterisation of the Bragg peak in proton beam radiotherapy

Alastair Crossley, Karen Habermann, Emma Horton +3

Proton beam radiotherapy stands at the forefront of precision cancer treatment, leveraging the unique physical interactions of proton beams with human tissue to deliver minimal dos…

cs.CV2024★ 13 cited

OMG-Net: A Deep Learning Framework Deploying Segment Anything to Detect Pan-Cancer Mitotic Figures from Haematoxylin and Eosin-Stained Slides

Zhuoyan Shen, Mikael Simard, Douglas Brand +14

Mitotic activity is an important feature for grading several cancer types. Counting mitotic figures (MFs) is a time-consuming, laborious task prone to inter-observer variation. Ina…

cs.HC2024★ 78 cited

Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology

Nur Yildirim, Hannah Richardson, Maria T. Wetscherek +18

Recent advances in AI combine large language models (LLMs) with vision encoders that bring forward unprecedented technical capabilities to leverage for a wide range of healthcare a…