collaborators

5 papers

cs.CV2026

Motion-Guided Causal Disentanglement for Robust Multi-View Cine Cardiac MRI Diagnosis

Chuankai Xu, Cristiane De Carvalho Singulane, Mohammad Abuannadi +10

Multi-view cardiac magnetic resonance (CMR) imaging provides complementary anatomical information and is widely used for noninvasive disease assessment. Recent transformer-based mo…

eess.IV2026

EchoJEPA: A Latent Predictive Foundation Model for Echocardiography

Alif Munim, Adibvafa Fallahpour, Teodora Szasz +9

Foundation models for echocardiography often struggle to disentangle anatomical signal from the stochastic speckle and acquisition artifacts inherent to ultrasound. We present Echo…

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

Learning to Stop: Reinforcement Learning for Efficient Patient-Level Echocardiographic Classification

Woo-Jin Cho Kim, Jorge Oliveira, Arian Beqiri +8

Guidelines for transthoracic echocardiographic examination recommend the acquisition of multiple video clips from different views of the heart, resulting in a large number of clips…

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…