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Automated Intracranial Thrombus Segmentation from CT Images of Patients with Acute Ischemic Stroke: A Dual-Channel nnU-Net Approach with Uncertainty Quantification

2026-01-25

Abstract excerpt

<h4>Background</h4> Automated thrombus segmentation on CT imaging could enable routine extraction of clot volume and other biomarkers in large vessel occlusion (LVO) stroke, but current deep learning models provide deterministic masks without indicating when their output is unreliable. We developed and evaluated an uncertainty-aware segmentation framework that couples nnU-Net with Bayesian-style uncertainty estim...

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Literature Corpus work: 7d2e1e2e-28c9-5a3f-b309-0d42716e1c6f
DOI: 10.64898/2026.01.23.26344730

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