ArticleScientific reports2020
Evaluating White Matter Lesion Segmentations with Refined Sørensen-Dice Analysis.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
72 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Vasculature segmentation in 3D hierarchical phase-contrast tomography images of human kidneys.Nature communications · 2026Pooled it
- AI-driven ablative margin assessment after HCC radiofrequency ablation: a case-control feasibility study.European radiology experimental · 2026Article
- Beyond the LUMIR challenge: The pathway to foundational registration models.Medical image analysis · 2026Article
- Real-time AI integration for MR to detect artifacts and guide pulse sequence adaptations.bioRxiv : the preprint server for biology · 2026Article
- A Soft-Robotic Biomimetic Benchtop Model for Esophageal Motility Simulation.Nature communications · 2026Article
- AutoPET Challenge on Fully Automated Lesion Segmentation in Oncologic PET/CT Imaging, Part 2: Domain Generalization.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2026Article
- Novel image registration approach for combining 2D Osterix and collagen bundles images with 3D micro-CT.JBMR plus · 2026Article
- UNISELF: A unified network with instance normalization and self-ensembled lesion fusion for multiple sclerosis lesion segmentation.Medical image analysis · 2026Article
- Greater Increase in Hippocampal Activity During the Early Postnatal Period After Preterm Birth Is Associated With Better Cognitive and Motor Outcomes at 18 Months.Developmental neurobiology · 2026Article
- A comparative study of deep learning for cortical lesion MRI segmentation with explainability analysis in multiple sclerosis.NeuroImage. Clinical · 2026Article
- Surrogate modeling of Cellular-Potts agent-based models as a segmentation task using the U-Net neural network architecture.PLoS computational biology · 2025Article
- Development and Validation of a Modality-Invariant 3D Swin U-Net Transformer for Liver and Spleen Segmentation on Multi-Site Clinical Bi-parametric MR Images.Journal of imaging informatics in medicine · 2025Article
- Article
- Article
- Splenic T2 signal intensity loss on MRI is associated with disease burden in multiple myeloma.European radiology · 2025Article
- 3D Hyperspectral Data Analysis with Spatially Aware Deep Learning for Diagnostic Applications.Analytical chemistry · 2025Article
- Effect of magnetic field strength and segmentation variability on the reproducibility and repeatability of radiomic texture features in cardiovascular magnetic resonance parametric mapping.The international journal of cardiovascular imaging · 2025Article
- A Method for Sensitivity Analysis of Automatic Contouring Algorithms Across Different MRI Contrast Weightings Using SyntheticMR.medRxiv : the preprint server for health sciences · 2025Article
- A laboratory feasibility study using a computer algorithm for anastomosis segmentation of epicardial ultrasonography images from distal coronary artery bypass anastomoses.Journal of cardiothoracic surgery · 2025Article
- Evaluation of potential of targeted sequencing through mutational signature simulation.PloS one · 2025Article
12 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors.
Funding
Abstract
The Sørensen-Dice index (SDI) is a widely used measure for evaluating medical image segmentation algorithms. It offers a standardized measure of segmentation accuracy which has proven useful. However, it offers diminishing insight when the number of objects is unknown, such as in white matter lesion segmentation of multiple sclerosis (MS) patients. We present a refinement for finer grained parsing of SDI results in situations where the number of objects is unknown. We explore these ideas with two case studies showing what can be learned from our two presented studies. Our first study explores an inter-rater comparison, showing that smaller lesions cannot be reliably identified. In our second case study, we demonstrate fusing multiple MS lesion segmentation algorithms based on the insights into the algorithms provided by our analysis to generate a segmentation that exhibits improved performance. This work demonstrates the wealth of information that can be learned from refined analysis of medical image segmentations.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.