arXiv Computer Vision
Longitudinal tracking of multiple sclerosis lesions in the spinal cord: A validation study
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arXiv Computer Vision
Oct 28
FORESEE-MS: Toward Prospective Spatial Forecasting of Future Multiple Sclerosis Lesions from Baseline FLAIR MRI
The paper introduces FORESEE-MS, a protocol for evaluating prospective spatial forecasting of future multiple sclerosis lesions using baseline FLAIR MRI. It compares a fold‑specific population‑prior atlas to five deep‑learning models (3D U‑Net, Attn+ResBlock+VAE, ViT, and two SwinUNETR variants) on voxel‑level discrimination (AUROC, AUPRC) and within‑patient lesion localization (Recall@Top‑K%). While the atlas achieved the best pooled AUROC and AUPRC, the 3D U‑Net and Attn+ResBlock+VAE showed higher within‑patient recall, though confidence intervals largely overlapped zero, leaving the benefit of patient‑specific predictive information uncertain in this small cohort.
arXiv AI
Jun 3
Efficient Transformer-Based Localized Patch Sampling for Choroid Plexus Segmentation in Multiple Sclerosis
arXiv:2606. 03566v1 Announce Type: cross Abstract: Background: The lateral ventricle choroid plexus (LVCP) is gaining recognition as a key imaging biomarker for multiple sclerosis (MS) related to physical disability and neuroinflammation.
arXiv Computer Vision
Oct 8
STRIDE: Spatial-Temporal Representation for Interval-conditioned Disease Evolution in Longitudinal Glioblastoma MRI
arXiv:2610.08848v1 Announce Type: cross Abstract: Glioblastoma (GBM), an aggressive primary brain tumor, is routinely monitored with longitudinal MRI after treatment. Distinguishing stable disease (S...
arXiv Computer Vision
Sep 22
DiaSeg: Diagonal Segment Extraction from DTW Paths for Interpretable Gait Analysis
DiaSeg extracts diagonal segments from Dynamic Time Warping (DTW) paths, characterizing each with five geometric features to preserve local alignment information. In a study of 91 subjects across six clinical conditions, these segments revealed consistent unsupervised patterns aligned with biomechanical phases and achieved near-perfect separation of healthy and pathological gait. While cycle‑based methods reached higher overall accuracy, DiaSeg offers phase‑specific interpretability, pinpointing where coordination breaks down within the gait cycle.
arXiv AI
Jun 9
A multi-agent system for spine MRI report generation from multi-sequence imaging
arXiv:2606. 08897v1 Announce Type: cross Abstract: Spinal pathology is a leading cause of pain and disability worldwide.
arXiv AI
Jun 9
Comparative evaluation of training strategies using partially labelled datasets for segmentation of white matter hyperintensities and stroke lesions in FLAIR MRI
arXiv:2601. 20503v2 Announce Type: replace-cross Abstract: White matter hyperintensities (WMH) and ischaemic stroke lesions (ISL) are key imaging biomarkers of cerebral small vessel disease (SVD) detectable on magnetic resonance imaging (MRI).