162 citations · 455 across the 51 of their papers we have counts for
24 papers · 1 filter
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…
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.…
Learned Local Attention Maps for Synthesising Vessel Segmentations
Yash Deo, Rodrigo Bonazzola, Haoran Dou +5
Magnetic resonance angiography (MRA) is an imaging modality for visualising blood vessels. It is useful for several diagnostic applications and for assessing the risk of adverse ev…
Shape-guided Conditional Latent Diffusion Models for Synthesising Brain Vasculature
Yash Deo, Haoran Dou, Nishant Ravikumar +2
The Circle of Willis (CoW) is the part of cerebral vasculature responsible for delivering blood to the brain. Understanding the diverse anatomical variations and configurations of…
Adaptive Semi-Supervised Segmentation of Brain Vessels with Ambiguous Labels
Fengming Lin, Yan Xia, Nishant Ravikumar +3
Accurate segmentation of brain vessels is crucial for cerebrovascular disease diagnosis and treatment. However, existing methods face challenges in capturing small vessels and hand…
Generative Adversarial Networks for Stain Normalisation in Histopathology
Jack Breen, Kieran Zucker, Katie Allen +2
The rapid growth of digital pathology in recent years has provided an ideal opportunity for the development of artificial intelligence-based tools to improve the accuracy and effic…
A Conditional Flow Variational Autoencoder for Controllable Synthesis of Virtual Populations of Anatomy
Haoran Dou, Nishant Ravikumar, Alejandro F. Frangi
The generation of virtual populations (VPs) of anatomy is essential for conducting in silico trials of medical devices. Typically, the generated VP should capture sufficient variab…
GSMorph: Gradient Surgery for cine-MRI Cardiac Deformable Registration
Haoran Dou, Ning Bi, Luyi Han +7
Deep learning-based deformable registration methods have been widely investigated in diverse medical applications. Learning-based deformable registration relies on weighted objecti…
Artificial Intelligence in Ovarian Cancer Histopathology: A Systematic Review
Jack Breen, Katie Allen, Kieran Zucker +5
Purpose - To characterise and assess the quality of published research evaluating artificial intelligence (AI) methods for ovarian cancer diagnosis or prognosis using histopatholog…
Efficient subtyping of ovarian cancer histopathology whole slide images using active sampling in multiple instance learning
Jack Breen, Katie Allen, Kieran Zucker +3
Weakly-supervised classification of histopathology slides is a computationally intensive task, with a typical whole slide image (WSI) containing billions of pixels to process. We p…
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…
Localizing the Recurrent Laryngeal Nerve via Ultrasound with a Bayesian Shape Framework
Haoran Dou, Luyi Han, Yushuang He +6
Tumor infiltration of the recurrent laryngeal nerve (RLN) is a contraindication for robotic thyroidectomy and can be difficult to detect via standard laryngoscopy. Ultrasound (US)…
Mitosis domain generalization in histopathology images -- The MIDOG challenge
Marc Aubreville, Nikolas Stathonikos, Christof A. Bertram +32
The density of mitotic figures within tumor tissue is known to be highly correlated with tumor proliferation and thus is an important marker in tumor grading. Recognition of mitoti…
Assessing domain adaptation techniques for mitosis detection in multi-scanner breast cancer histopathology images
Jack Breen, Kieran Zucker, Nicolas M. Orsi +1
Breast cancer is the most commonly diagnosed cancer worldwide, with over two million new cases each year. During diagnostic tumour grading, pathologists manually count the number o…
Style Curriculum Learning for Robust Medical Image Segmentation
Zhendong Liu, Van Manh, Xin Yang +6
The performance of deep segmentation models often degrades due to distribution shifts in image intensities between the training and test data sets. This is particularly pronounced…
A Deep Discontinuity-Preserving Image Registration Network
Xiang Chen, Nishant Ravikumar, Yan Xia +1
Image registration aims to establish spatial correspondence across pairs, or groups of images, and is a cornerstone of medical image computing and computer-assisted-interventions.…
CAR-Net: Unsupervised Co-Attention Guided Registration Network for Joint Registration and Structure Learning
Xiang Chen, Yan Xia, Nishant Ravikumar +1
Image registration is a fundamental building block for various applications in medical image analysis. To better explore the correlation between the fixed and moving images and imp…
Spatio-temporal Multi-task Learning for Cardiac MRI Left Ventricle Quantification
Sulaiman Vesal, Mingxuan Gu, Andreas Maier +1
Quantitative assessment of cardiac left ventricle (LV) morphology is essential to assess cardiac function and improve the diagnosis of different cardiovascular diseases. In current…
Cardiac Segmentation on Late Gadolinium Enhancement MRI: A Benchmark Study from Multi-Sequence Cardiac MR Segmentation Challenge
Xiahai Zhuang, Jiahang Xu, Xinzhe Luo +20
Accurate computing, analysis and modeling of the ventricles and myocardium from medical images are important, especially in the diagnosis and treatment management for patients suff…
COPD Classification in CT Images Using a 3D Convolutional Neural Network
Jalil Ahmed, Sulaiman Vesal, Felix Durlak +4
Chronic obstructive pulmonary disease (COPD) is a lung disease that is not fully reversible and one of the leading causes of morbidity and mortality in the world. Early detection a…
Analyzing an Imitation Learning Network for Fundus Image Registration Using a Divide-and-Conquer Approach
Siming Bayer, Xia Zhong, Weilin Fu +2
Comparison of microvascular circulation on fundoscopic images is a non-invasive clinical indication for the diagnosis and monitoring of diseases, such as diabetes and hypertensions…
Coronary Artery Plaque Characterization from CCTA Scans using Deep Learning and Radiomics
Felix Denzinger, Michael Wels, Nishant Ravikumar +6
Assessing coronary artery plaque segments in coronary CT angiography scans is an important task to improve patient management and clinical outcomes, as it can help to decide whethe…
Automated Multi-sequence Cardiac MRI Segmentation Using Supervised Domain Adaptation
Sulaiman Vesal, Nishant Ravikumar, Andreas Maier
Left ventricle segmentation and morphological assessment are essential for improving diagnosis and our understanding of cardiomyopathy, which in turn is imperative for reducing ris…
Dilated deeply supervised networks for hippocampus segmentation in MRI
Lukas Folle, Sulaiman Vesal, Nishant Ravikumar +1
Tissue loss in the hippocampi has been heavily correlated with the progression of Alzheimer's Disease (AD). The shape and structure of the hippocampus are important factors in term…