36 citations · 57 across the 19 of their papers we have counts for
8 papers · 1 filter
A Symmetric Dynamic Learning Framework for Diffeomorphic Medical Image Registration
Jinqiu Deng, Ke Chen, Mingke Li +4
Diffeomorphic image registration is crucial for various medical imaging applications because it can preserve the topology of the transformation. This study introduces DCCNN-LSTM-Re…
Integrating Deep Learning with Fundus and Optical Coherence Tomography for Cardiovascular Disease Prediction
Cynthia Maldonado-Garcia, Arezoo Zakeri, Alejandro F Frangi +1
Early identification of patients at risk of cardiovascular diseases (CVD) is crucial for effective preventive care, reducing healthcare burden, and improving patients' quality of l…
Statistical Distance-Guided Unsupervised Domain Adaptation for Automated Multi-Class Cardiovascular Magnetic Resonance Image Quality Assessment
Shahabedin Nabavi, Kian Anvari Hamedani, Mohsen Ebrahimi Moghaddam +2
This study proposes an attention-based statistical distance-guided unsupervised domain adaptation model for multi-class cardiovascular magnetic resonance (CMR) image quality assess…
Multiple Teachers-Meticulous Student: A Domain Adaptive Meta-Knowledge Distillation Model for Medical Image Classification
Shahabedin Nabavi, Kian Anvari Hamedani, Mohsen Ebrahimi Moghaddam +2
Background: Image classification can be considered one of the key pillars of medical image analysis. Deep learning (DL) faces challenges that prevent its practical applications des…
An End-to-End Deep Learning Generative Framework for Refinable Shape Matching and Generation
Soodeh Kalaie, Andy Bulpitt, Alejandro F. Frangi +1
Generative modelling for shapes is a prerequisite for In-Silico Clinical Trials (ISCTs), which aim to cost-effectively validate medical device interventions using synthetic anatomi…
Predicting risk of cardiovascular disease using retinal OCT imaging
Cynthia Maldonado-Garcia, Rodrigo Bonazzola, Enzo Ferrante +4
Cardiovascular diseases (CVD) are the leading cause of death globally. Non-invasive, cost-effective imaging techniques play a crucial role in early detection and prevention of CVD.…
GS-EMA: Integrating Gradient Surgery Exponential Moving Average with Boundary-Aware Contrastive Learning for Enhanced Domain Generalization in Aneurysm Segmentation
Fengming Lin, Yan Xia, Michael MacRaild +6
The automated segmentation of cerebral aneurysms is pivotal for accurate diagnosis and treatment planning. Confronted with significant domain shifts and class imbalance in 3D Rotat…
Unsupervised Domain Adaptation for Brain Vessel Segmentation through Transwarp Contrastive Learning
Fengming Lin, Yan Xia, Michael MacRaild +6
Unsupervised domain adaptation (UDA) aims to align the labelled source distribution with the unlabelled target distribution to obtain domain-invariant predictive models. Since cros…