63 citations · 135 across the 25 of their papers we have counts for
6 papers · 1 filter
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…