162 citations · 455 across the 51 of their papers we have counts for
13 papers · 1 filter
Radiology Report Generation Using Transformers Conditioned with Non-imaging Data
Nurbanu Aksoy, Nishant Ravikumar, Alejandro F Frangi
Medical image interpretation is central to most clinical applications such as disease diagnosis, treatment planning, and prognostication. In clinical practice, radiologists examine…
Beyond Images: An Integrative Multi-modal Approach to Chest X-Ray Report Generation
Nurbanu Aksoy, Serge Sharoff, Selcuk Baser +2
Image-to-text radiology report generation aims to automatically produce radiology reports that describe the findings in medical images. Most existing methods focus solely on the im…
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…
Implicit Visual Bias Mitigation by Posterior Estimate Sharpening of a Bayesian Neural Network
Rebecca S Stone, Nishant Ravikumar, Andrew J Bulpitt +1
The fairness of a deep neural network is strongly affected by dataset bias and spurious correlations, both of which are usually present in modern feature-rich and complex visual da…
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…
Learning disentangled representations for explainable chest X-ray classification using Dirichlet VAEs
Rachael Harkness, Alejandro F Frangi, Kieran Zucker +1
This study explores the use of the Dirichlet Variational Autoencoder (DirVAE) for learning disentangled latent representations of chest X-ray (CXR) images. Our working hypothesis i…
Unsupervised ensemble-based phenotyping helps enhance the discoverability of genes related to heart morphology
Rodrigo Bonazzola, Enzo Ferrante, Nishant Ravikumar +5
Recent genome-wide association studies (GWAS) have been successful in identifying associations between genetic variants and simple cardiac parameters derived from cardiac magnetic…