activity
20212025
most citedFourier-Net+: Leveraging Band-Limited Representation for Efficient 3D Medical Image Registration

3 citations · 3 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2025

Anatomically Constrained Transformers for Echocardiogram Analysis

Alexander Thorley, Agis Chartsias, Jordan Strom +4

Video transformers have recently demonstrated strong potential for echocardiogram (echo) analysis, leveraging self-supervised pre-training and flexible adaptation across diverse ta…

cs.CV2025

Anatomically Constrained Transformers for Cardiac Amyloidosis Classification

Alexander Thorley, Agis Chartsias, Jordan Strom +7

Cardiac amyloidosis (CA) is a rare cardiomyopathy, with typical abnormalities in clinical measurements from echocardiograms such as reduced global longitudinal strain of the myocar…

cs.AI2025

A Language-Signal-Vision Multimodal Framework for Multitask Cardiac Analysis

Yuting Zhang, Tiantian Geng, Luoying Hao +9

Contemporary cardiovascular management involves complex consideration and integration of multimodal cardiac datasets, where each modality provides distinct but complementary physio…

cs.AI2025

CardAIc-Agents: A Multimodal Framework with Hierarchical Adaptation for Cardiac Care Support

Yuting Zhang, Karina V. Bunting, Asgher Champsi +8

Cardiovascular diseases (CVDs) remain the foremost cause of mortality worldwide, a burden worsened by a severe deficit of healthcare workers. Artificial intelligence (AI) agents ha…

cs.CV2024

Development of Automated Neural Network Prediction for Echocardiographic Left ventricular Ejection Fraction

Yuting Zhang, Boyang Liu, Karina V. Bunting +11

The echocardiographic measurement of left ventricular ejection fraction (LVEF) is fundamental to the diagnosis and classification of patients with heart failure (HF). In order to q…

eess.IV2023★ 3 cited

Fourier-Net+: Leveraging Band-Limited Representation for Efficient 3D Medical Image Registration

Xi Jia, Alexander Thorley, Alberto Gomez +3

U-Net style networks are commonly utilized in unsupervised image registration to predict dense displacement fields, which for high-resolution volumetric image data is a resource-in…

cs.CV2021

Nesterov Accelerated ADMM for Fast Diffeomorphic Image Registration

Alexander Thorley, Xi Jia, Hyung Jin Chang +8

Deterministic approaches using iterative optimisation have been historically successful in diffeomorphic image registration (DiffIR). Although these approaches are highly accurate,…