What does this research mean for the field?

Newly developed deep learning-based white matter hyperintensity segmentation algorithms based on MD-GRU and nnU-Net outperform current state-of-the-art tools in accuracy, precision, and statistical power for detecting treatment effects. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

January 1, 2025Cerebral Circulation - Cognition and BehaviorOpen Access

Technical and clinical validation of a novel deep learning-based white matter hyperintensity segmentation tool

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Authors

BGBenno GesierichUniversity of Basel LPLukas PirpamerUniversity of Basel DMDominik MeierBinghamton University

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Cite This Study

Gesierich et al. (2025) studied this question.

synapsesocial.com/papers/6a238a1355bd20cf6fa5f539 https://doi.org/10.1016/j.cccb.2025.100393

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January 1, 2025Cerebral Circulation - Cognition and BehaviorOpen Access

Technical and clinical validation of a novel deep learning-based white matter hyperintensity segmentation tool

View Full Paper

Ask AI

Bookmark

Authors

BGBenno GesierichUniversity of Basel LPLukas PirpamerUniversity of Basel DMDominik MeierBinghamton University

Discussion

Member takes

Implication

Key Points

Key points are not available for this paper at this time.

Cite This Study

Gesierich et al. (2025) studied this question.

synapsesocial.com/papers/6a238a1355bd20cf6fa5f539 https://doi.org/10.1016/j.cccb.2025.100393

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