37 citations · 90 across the 27 of their papers we have counts for
31 papers
CardioDrift: Automatic Cardiac Motion Tracking on a 3D Atlas Mesh via Shape-aware Coherent Point Drift with Slice Shift Correction
Reza Akbari Movahed, Abuzar Rezaee, Shatha Alamri +3
Automatic cardiac motion tracking from cine cardiac magnetic resonance (CMR) imaging is essential for quantifying myocardial motion abnormalities associated with cardiovascular dis…
SpikePose: Lightweight Video Human Pose Estimation
Yunhao Huang, Kaushik Bhargav Sivangi, Tianyi Yu +1
Efficient video human pose estimation must balance localisation accuracy, motion quality, and energy cost. We present SpikePose, a lightweight video pose estimator that pairs a fra…
NormMoX: A Normative Mixture of Experts for Explainable Autism Classification from Structural and Functional MRI
Muhammad Hasan Masrur, Fani Deligianni
While structural and functional magnetic resonance imaging (sMRI, fMRI) offer profound potential for researching autism spectrum disorder (ASD) and understanding individual neurodi…
Beat-ssl: Capturing Local ECG Morphology through Heartbeat-level Contrastive Learning with Soft Targets
Muhammad Ilham Rizqyawan, Peter Macfarlane, Stathis Hadjidemetriou +1
Obtaining labelled ECG data for developing supervised models is challenging. Contrastive learning (CL) has emerged as a promising pretraining approach that enables effective transf…
Your Eyes Controlled the Game: Real-Time Cognitive Training Adaptation based on Eye-Tracking and Physiological Data in Virtual Reality
Dominik Szczepaniak, Monika Harvey, Fani Deligianni
Cognitive training for sustained attention and working memory is vital across domains relying on robust mental capacity such as education or rehabilitation. Adaptive systems are es…
Cross-Subject and Cross-Montage EEG Transfer Learning via Individual Tangent Space Alignment and Spatial-Riemannian Feature Fusion
Nicole Lai-Tan, Xiao Gu, Marios G. Philiastides +1
Personalised music-based interventions offer a powerful means of supporting motor rehabilitation by dynamically tailoring auditory stimuli to provide external timekeeping cues, mod…
Grounding Chest X-Ray Visual Question Answering with Generated Radiology Reports
Francesco Dalla Serra, Patrick Schrempf, Chaoyang Wang +3
We present a novel approach to Chest X-ray (CXR) Visual Question Answering (VQA), addressing both single-image image-difference questions. Single-image questions focus on abnormali…
Differentially Private 2D Human Pose Estimation
Kaushik Bhargav Sivangi, Paul Henderson, Fani Deligianni
Human pose estimation (HPE) has become essential in numerous applications including healthcare, activity recognition, and human-computer interaction. However, the privacy implicati…
Predicting Cardiopulmonary Exercise Testing Outcomes in Congenital Heart Disease Through Multi-modal Data Integration and Geometric Learning
Muhammet Alkan, Gruschen Veldtman, Fani Deligianni
Cardiopulmonary exercise testing (CPET) provides a comprehensive assessment of functional capacity by measuring key physiological variables including oxygen consumption (), c…
Electronic Health Records: Towards Digital Twins in Healthcare
Muhammet Alkan, Hester Huijsdens, Yola Jones +1
The pivotal shift from traditional paper-based records to sophisticated Electronic Health Records (EHR), enabled systematic collection and analysis of patient data through descript…
Artificial Intelligence-Driven Clinical Decision Support Systems
Muhammet Alkan, Idris Zakariyya, Samuel Leighton +3
As artificial intelligence (AI) becomes increasingly embedded in healthcare delivery, this chapter explores the critical aspects of developing reliable and ethical Clinical Decisio…
Differentially Private Integrated Decision Gradients (IDG-DP) for Radar-based Human Activity Recognition
Idris Zakariyya, Linda Tran, Kaushik Bhargav Sivangi +2
Human motion analysis offers significant potential for healthcare monitoring and early detection of diseases. The advent of radar-based sensing systems has captured the spotlight f…
Learning Semi-Supervised Medical Image Segmentation from Spatial Registration
Qianying Liu, Paul Henderson, Xiao Gu +2
Semi-supervised medical image segmentation has shown promise in training models with limited labeled data and abundant unlabeled data. However, state-of-the-art methods ignore a po…
GLFNET: Global-Local (frequency) Filter Networks for efficient medical image segmentation
Athanasios Tragakis, Qianying Liu, Chaitanya Kaul +5
We propose a novel transformer-style architecture called Global-Local Filter Network (GLFNet) for medical image segmentation and demonstrate its state-of-the-art performance. We re…
Riemannian Prediction of Anatomical Diagnoses in Congenital Heart Disease based on 12-lead ECGs
Muhammet Alkan, Gruschen Veldtman, Fani Deligianni
Congenital heart disease (CHD) is a relatively rare disease that affects patients at birth and results in extremely heterogeneous anatomical and functional defects. 12-lead ECG sig…
Controllable Chest X-Ray Report Generation from Longitudinal Representations
Francesco Dalla Serra, Chaoyang Wang, Fani Deligianni +2
Radiology reports are detailed text descriptions of the content of medical scans. Each report describes the presence/absence and location of relevant clinical findings, commonly in…
Consensus of state of the art mortality prediction models: From all-cause mortality to sudden death prediction
Yola Jones, Fani Deligianni, Jeff Dalton +2
Worldwide, many millions of people die suddenly and unexpectedly each year, either with or without a prior history of cardiovascular disease. Such events are sparse (once in a life…
Finding-Aware Anatomical Tokens for Chest X-Ray Automated Reporting
Francesco Dalla Serra, Chaoyang Wang, Fani Deligianni +2
The task of radiology reporting comprises describing and interpreting the medical findings in radiographic images, including description of their location and appearance. Automated…
Multi-Scale Cross Contrastive Learning for Semi-Supervised Medical Image Segmentation
Qianying Liu, Xiao Gu, Paul Henderson +1
Semi-supervised learning has demonstrated great potential in medical image segmentation by utilizing knowledge from unlabeled data. However, most existing approaches do not explici…
Towards personalised music-therapy; a neurocomputational modelling perspective
Nicole Lai, Marios Philiastides, Fahim Kawsar +1
Music therapy has emerged recently as a successful intervention that improves patient's outcome in a large range of neurological and mood disorders without adverse effects. Brain n…
Threat Perception Modulation by Capturing Emotion, Motor and Empathetic System Responses: A Systematic Review
Elizabeth M. Jacobs, Fani Deligianni., Frank Pollick
The fight or flight phenomena is of evolutionary origin and responsible for the type of defensive behaviours enacted, when in the face of threat. This review attempts to draw the l…
Optimizing Vision Transformers for Medical Image Segmentation
Qianying Liu, Chaitanya Kaul, Jun Wang +3
For medical image semantic segmentation (MISS), Vision Transformers have emerged as strong alternatives to convolutional neural networks thanks to their inherent ability to capture…
Adversarial Attention for Human Motion Synthesis
Matthew Malek-Podjaski, Fani Deligianni
Analysing human motions is a core topic of interest for many disciplines, from Human-Computer Interaction, to entertainment, Virtual Reality and healthcare. Deep learning has achie…
Improving ECG Classification Interpretability using Saliency Maps
Yola Jones, Fani Deligianni, Jeff Dalton
Cardiovascular disease is a large worldwide healthcare issue; symptoms often present suddenly with minimal warning. The electrocardiogram (ECG) is a fast, simple and reliable metho…