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Ischemic Stroke Segmentation and Net Water Uptake Quantification on Multicenter Non-Contrast CT Using Supervised Target-Domain Adaptation

Research Medical/Healthcare AI

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TL;DR - A multicenter study developed an nnU-Net-based, target-domain-adapted model to segment ischemic stroke lesions and quantify net water uptake directly from non-contrast CT. The approach could reduce reliance on advanced imaging, though segmentation accuracy varied substantially by dataset and lesion size.

  • Evaluated retrospectively on 801 patients across four datasets, with fine-tuning on small target-domain subsets from Boston and ISLES.
  • For lesions ≥30 mL, median Dice scores were 0.68 on Boston data and 0.56 on ISLES.
  • Performance declined when smaller lesions were included: median Dice was 0.54 for acute lesions in Boston and 0.20 against post-treatment infarcts in ISLES.
  • Automated net water uptake estimation achieved a mean absolute error of 1.37 percentage points on the Boston cohort.

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Ischemic Stroke Segmentation and Net Water Uptake Quantification on Multicenter Non-Contrast CT Using Supervised Target-Domain Adaptation

arXiv cs.CV Linus Britt, Maximilian Nielsen, Susan Klapproth, Andre Kemmling, Michael H. Lev, Gabriel Broocks, Rene Werner, Thilo Sentker 2026-09-17 arXiv:2609.20151
Public signals Semantic Scholar citations 0 · Semantic Scholar influential citations 0
Providers: Hugging Face · N/A OpenAlex · N/A Publisher · N/A Semantic Scholar · Citations 0 · Influential citations 0 X · N/A Fetched 2026-09-22 14:18:55.636204 UTC

TL;DR - A multicenter study developed an nnU-Net-based, target-domain-adapted model to segment ischemic stroke lesions and quantify net water uptake directly from non-contrast CT. The approach could reduce reliance on advanced imaging, though segmentation accuracy varied substantially by dataset and lesion size.

  • Evaluated retrospectively on 801 patients across four datasets, with fine-tuning on small target-domain subsets from Boston and ISLES.
  • For lesions ≥30 mL, median Dice scores were 0.68 on Boston data and 0.56 on ISLES.
  • Performance declined when smaller lesions were included: median Dice was 0.54 for acute lesions in Boston and 0.20 against post-treatment infarcts in ISLES.
  • Automated net water uptake estimation achieved a mean absolute error of 1.37 percentage points on the Boston cohort.
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