Publications
Category: Multiple Sclerosis
Fully automatic detection and quantification of new white matter lesions using deep learning
Accurate detection, segmentation, and quantification of lesion dynamics in longitudinal MRI is crucial for monitoring disease progression in Multiple Sclerosis, and for evaluating the efficacy of therapeutic interventions. We present an efficient, automatic method utilising deep learning to assess lesion changes in FLAIR MRI with a high degree of accuracy.
A convolutional neural network-based framework for imaging biomarkers in MS - white matter hyperintensity & brain region volumes
Summary: We developed and validated scalable and robust methods for automated volumetric analysis of brain white matter hyperintensities (T2 lesions) and regions of interest in multiple sclerosis.