activity
20162024
most citedUPL-SFDA: Uncertainty-aware Pseudo Label Guided Source-Free Domain Adaptation for Medical Image Segmentation

61 citations · 157 across the 18 of their papers we have counts for

collaborators

18 papers

eess.IV2024

SAM-I2I: Unleash the Power of Segment Anything Model for Medical Image Translation

Jiayu Huo, Sebastien Ourselin, Rachel Sparks

Medical image translation is crucial for reducing the need for redundant and expensive multi-modal imaging in clinical field. However, current approaches based on Convolutional Neu…

cs.CV20244 cited

A self-supervised text-vision framework for automated brain abnormality detection

David A. Wood, Emily Guilhem, Sina Kafiabadi +13

Artificial neural networks trained on large, expert-labelled datasets are considered state-of-the-art for a range of medical image recognition tasks. However, categorically labelle…

cs.CV2024

Framework to generate perfusion map from CT and CTA images in patients with acute ischemic stroke: A longitudinal and cross-sectional study

Chayanin Tangwiriyasakul, Pedro Borges, Stefano Moriconi +6

Stroke is a leading cause of disability and death. Effective treatment decisions require early and informative vascular imaging. 4D perfusion imaging is ideal but rarely available…

cs.CV2024

RetiGen: A Framework for Generalized Retinal Diagnosis Using Multi-View Fundus Images

Ze Chen, Gongyu Zhang, Jiayu Huo +7

This study introduces a novel framework for enhancing domain generalization in medical imaging, specifically focusing on utilizing unlabelled multi-view colour fundus photographs.…

cs.CV20241 cited

DDSB: An Unsupervised and Training-free Method for Phase Detection in Echocardiography

Zhenyu Bu, Yang Liu, Jiayu Huo +7

Accurate identification of End-Diastolic (ED) and End-Systolic (ES) frames is key for cardiac function assessment through echocardiography. However, traditional methods face severa…

cs.CV20241 cited

SuPRA: Surgical Phase Recognition and Anticipation for Intra-Operative Planning

Maxence Boels, Yang Liu, Prokar Dasgupta +2

Intra-operative recognition of surgical phases holds significant potential for enhancing real-time contextual awareness in the operating room. However, we argue that online recogni…