Abstract Machine learning (ML) algorithms have made a tremendous impact in the field of
medical imaging. While medical imaging datasets have been growing in size, a challenge …

Multiple-instance learning (MIL) is a recent machine-learning paradigm that is particularly
well suited to medical image and video analysis (MIVA) tasks. Based solely on class labels …

Structural magnetic resonance imaging (sMRI) is widely used for the brain neurological
disease diagnosis, which could reflect the variations of brain. However, due to the local …

Recurrent neuroinflammation in relapsing-remitting MS (RRMS) is thought to lead to
neurodegeneration, resulting in progressive disability. Repeated magnetic resonance …

Cerebral small vessel disease (SVD) can manifest in a number of ways. Many of these result
in hyperintense regions visible on T 2-weighted magnetic resonance (MR) images. The …

In the brain, enlarged perivascular spaces (PVS) relate to cerebral small vessel disease
(SVD), poor cognition, inflammation and hypertension. We propose a fully automatic scheme …

Introduction: Multiple sclerosis (MS) is a chronic neuroinflammatory and neurodegenerative
disease. MS prevalence varies geographically and is notably high in Scotland. Disease …

Purpose To validate a random forest method for segmenting cerebral white matter lesions
(WMLs) on computed tomographic (CT) images in a multicenter cohort of patients with acute …

Precise detection and quantification of white matter hyperintensity (WMH) is of great interest
in studies of neurological and vascular disorders. In this work, we propose a novel method …

Abstract Multiple Instance Learning (MIL) is a learning paradigm, where training instances
are arranged in sets, called bags, and only bag-level labels are available during training …