260 citations · 262 across the 5 of their papers we have counts for
5 papers
SegHeD: Segmentation of Heterogeneous Data for Multiple Sclerosis Lesions with Anatomical Constraints
Berke Doga Basaran, Xinru Zhang, Paul M. Matthews +1
Assessment of lesions and their longitudinal progression from brain magnetic resonance (MR) images plays a crucial role in diagnosing and monitoring multiple sclerosis (MS). Machin…
LesionMix: A Lesion-Level Data Augmentation Method for Medical Image Segmentation
Berke Doga Basaran, Weitong Zhang, Mengyun Qiao +3
Data augmentation has become a de facto component of deep learning-based medical image segmentation methods. Most data augmentation techniques used in medical imaging focus on spat…
Subject-Specific Lesion Generation and Pseudo-Healthy Synthesis for Multiple Sclerosis Brain Images
Berke Doga Basaran, Mengyun Qiao, Paul M. Matthews +1
Understanding the intensity characteristics of brain lesions is key for defining image-based biomarkers in neurological studies and for predicting disease burden and outcome. In th…
Generative Modelling of the Ageing Heart with Cross-Sectional Imaging and Clinical Data
Mengyun Qiao, Berke Doga Basaran, Huaqi Qiu +6
Cardiovascular disease, the leading cause of death globally, is an age-related disease. Understanding the morphological and functional changes of the heart during ageing is a key s…
Automatic Sleep Stage Scoring with Single-Channel EEG Using Convolutional Neural Networks
Orestis Tsinalis, Paul M. Matthews, Yike Guo +1
We used convolutional neural networks (CNNs) for automatic sleep stage scoring based on single-channel electroencephalography (EEG) to learn task-specific filters for classificatio…