63 citations · 135 across the 25 of their papers we have counts for
27 papers
DIGS: Distribution-Informed Gaussian Splatting for Training-Free Open-Vocabulary 3D Segmentation
Zhifan Zeng, Wenbo Xiao, Arcot Sowmya +1
Open-vocabulary 3D Gaussian segmentation typically binds semantic features to the per-Gaussian state via per-scene gradient training (1-4 h) or the more recent closed-form distilla…
Preserving Anatomical Continuity: Three-Stage Pipeline for Colon Segmentation in 3D Abdominal CT Scans
Deshan Kalupahana, Sonit Singh, Praveen Ravindran +1
Accurate colon segmentation from CT images is essential for colorectal disease analysis, yet deep learning based methods often produce disconnected predictions due to complex anato…
YOLO11-4K: An Efficient Architecture for Real-Time Small Object Detection in 4K Panoramic Images
Huma Hafeez, Matthew Garratt, Jo Plested +2
The processing of omnidirectional 360-degree images poses significant challenges for object detection due to inherent spatial distortions, wide fields of view, and ultra-high-resol…
Predicting Coronary Artery Calcium Severity based on Non-Contrast Cardiac CT images using Deep Learning
Lachlan Nguyen, Aidan Cousins, Arcot Sowmya +2
Cardiovascular disease causes high rates of mortality worldwide. Coronary artery calcium (CAC) scoring is a powerful tool to stratify the risk of atherosclerotic cardiovascular dis…
GazeDETR: Gaze Detection using Disentangled Head and Gaze Representations
Ryan Anthony Jalova de Belen, Gelareh Mohammadi, Arcot Sowmya
Gaze communication plays a crucial role in daily social interactions. Quantifying this behavior can help in human-computer interaction and digital phenotyping. While end-to-end mod…
LWT-ARTERY-LABEL: A Lightweight Framework for Automated Coronary Artery Identification
Shisheng Zhang, Ramtin Gharleghi, Sonit Singh +4
Coronary artery disease (CAD) remains the leading cause of death globally, with computed tomography coronary angiography (CTCA) serving as a key diagnostic tool. However, coronary…
GRAPHITE: Graph-Based Interpretable Tissue Examination for Enhanced Explainability in Breast Cancer Histopathology
Raktim Kumar Mondol, Ewan K. A. Millar, Peter H. Graham +3
Explainable AI (XAI) in medical histopathology is essential for enhancing the interpretability and clinical trustworthiness of deep learning models in cancer diagnosis. However, th…
Multi-omics data integration for early diagnosis of hepatocellular carcinoma (HCC) using machine learning
Annette Spooner, Mohammad Karimi Moridani, Azadeh Safarchi +4
The complementary information found in different modalities of patient data can aid in more accurate modelling of a patient's disease state and a better understanding of the underl…
Region Guided Attention Network for Retinal Vessel Segmentation
Syed Javed, Tariq M. Khan, Abdul Qayyum +2
Retinal imaging has emerged as a promising method of addressing this challenge, taking advantage of the unique structure of the retina. The retina is an embryonic extension of the…
Advancing Medical Image Segmentation with Mini-Net: A Lightweight Solution Tailored for Efficient Segmentation of Medical Images
Syed Javed, Tariq M. Khan, Abdul Qayyum +3
Accurate segmentation of anatomical structures and abnormalities in medical images is crucial for computer-aided diagnosis and analysis. While deep learning techniques excel at thi…
MM-SurvNet: Deep Learning-Based Survival Risk Stratification in Breast Cancer Through Multimodal Data Fusion
Raktim Kumar Mondol, Ewan K. A. Millar, Arcot Sowmya +1
Survival risk stratification is an important step in clinical decision making for breast cancer management. We propose a novel deep learning approach for this purpose by integratin…
BioFusionNet: Deep Learning-Based Survival Risk Stratification in ER+ Breast Cancer Through Multifeature and Multimodal Data Fusion
Raktim Kumar Mondol, Ewan K. A. Millar, Arcot Sowmya +1
Breast cancer is a significant health concern affecting millions of women worldwide. Accurate survival risk stratification plays a crucial role in guiding personalised treatment de…
Automatic 3D Multi-modal Ultrasound Segmentation of Human Placenta using Fusion Strategies and Deep Learning
Sonit Singh, Gordon Stevenson, Brendan Mein +2
Purpose: Ultrasound is the most commonly used medical imaging modality for diagnosis and screening in clinical practice. Due to its safety profile, noninvasive nature and portabili…
Assessing Encoder-Decoder Architectures for Robust Coronary Artery Segmentation
Shisheng Zhang, Ramtin Gharleghi, Sonit Singh +2
Coronary artery diseases are among the leading causes of mortality worldwide. Timely and accurate diagnosis, facilitated by precise coronary artery segmentation, is pivotal in chan…
Attention and Pooling based Sigmoid Colon Segmentation in 3D CT images
Md Akizur Rahman, Sonit Singh, Kuruparan Shanmugalingam +4
Segmentation of the sigmoid colon is a crucial aspect of treating diverticulitis. It enables accurate identification and localisation of inflammation, which in turn helps healthcar…
Visual Question Answering in the Medical Domain
Louisa Canepa, Sonit Singh, Arcot Sowmya
Medical visual question answering (Med-VQA) is a machine learning task that aims to create a system that can answer natural language questions based on given medical images. Althou…
hist2RNA: An efficient deep learning architecture to predict gene expression from breast cancer histopathology images
Raktim Kumar Mondol, Ewan K. A. Millar, Peter H Graham +3
Gene expression can be used to subtype breast cancer with improved prediction of risk of recurrence and treatment responsiveness over that obtained using routine immunohistochemist…
Computed tomography coronary angiogram images, annotations and associated data of normal and diseased arteries
Ramtin Gharleghi, Dona Adikari, Katy Ellenberger +5
Computed Tomography Coronary Angiography (CTCA) is a non-invasive method to evaluate coronary artery anatomy and disease. CTCA is ideal for geometry reconstruction to create virtua…
Temporal Pattern Mining for Analysis of Longitudinal Clinical Data: Identifying Risk Factors for Alzheimer's Disease
Annette Spooner, Gelareh Mohammadi, Perminder S. Sachdev +2
A novel framework is proposed for handling the complex task of modelling and analysis of longitudinal, multivariate, heterogeneous clinical data. This method uses temporal abstract…
Ensemble feature selection with clustering for analysis of high-dimensional, correlated clinical data in the search for Alzheimer's disease biomarkers
Annette Spooner, Gelareh Mohammadi, Perminder S. Sachdev +2
Healthcare datasets often contain groups of highly correlated features, such as features from the same biological system. When feature selection is applied to these datasets to ide…
Ensemble feature selection with data-driven thresholding for Alzheimer's disease biomarker discovery
Annette Spooner, Gelareh Mohammadi, Perminder S. Sachdev +2
Healthcare datasets present many challenges to both machine learning and statistics as their data are typically heterogeneous, censored, high-dimensional and have missing informati…
Multi-scale alignment and Spatial ROI Module for COVID-19 Diagnosis
Hongyan Xu, Dadong Wang, Arcot Sowmya
Coronavirus Disease 2019 (COVID-19) has spread globally and become a health crisis faced by humanity since first reported. Radiology imaging technologies such as computer tomograph…
Organ localisation using supervised and semi supervised approaches combining reinforcement learning with imitation learning
Sankaran Iyer, Alan Blair, Laughlin Dawes +3
Computer aided diagnostics often requires analysis of a region of interest (ROI) within a radiology scan, and the ROI may be an organ or a suborgan. Although deep learning algorith…
Video Generative Adversarial Networks: A Review
Nuha Aldausari, Arcot Sowmya, Nadine Marcus +1
With the increasing interest in the content creation field in multiple sectors such as media, education, and entertainment, there is an increasing trend in the papers that uses AI…