36 citations · 57 across the 19 of their papers we have counts for
9 papers · 1 filter
Metrics that matter: Evaluating image quality metrics for medical image generation
Yash Deo, Yan Jia, Toni Lassila +5
Evaluating generative models for synthetic medical imaging is crucial yet challenging, especially given the high standards of fidelity, anatomical accuracy, and safety required for…
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…
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.…
Multi-view Hybrid Graph Convolutional Network for Volume-to-mesh Reconstruction in Cardiovascular MRI
Nicolás Gaggion, Benjamin A. Matheson, Yan Xia +6
Cardiovascular magnetic resonance imaging is emerging as a crucial tool to examine cardiac morphology and function. Essential to this endeavour are anatomical 3D surface and volume…
A Generative Shape Compositional Framework to Synthesise Populations of Virtual Chimaeras
Haoran Dou, Seppo Virtanen, Nishant Ravikumar +1
Generating virtual populations of anatomy that capture sufficient variability while remaining plausible is essential for conducting in-silico trials of medical devices. However, no…
CS2-Net: Deep Learning Segmentation of Curvilinear Structures in Medical Imaging
Lei Mou, Yitian Zhao, Huazhu Fu +9
Automated detection of curvilinear structures, e.g., blood vessels or nerve fibres, from medical and biomedical images is a crucial early step in automatic image interpretation ass…