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DuoPIC system creates uncertainty-aware digital twins of cerebral perfusion

Researchers have developed DuoPIC, a novel digital twin system designed to create voxel-level digital twins of cerebral perfusion. This system integrates a Windkessel flow model with a tracer transport partial differential equation, incorporating a population-level neural closure to divide regions into fast and slow pathways. DuoPIC quantifies uncertainty in its estimates and has demonstrated state-of-the-art performance in lesion detection on ISLES'17 MR and ISLES'24 CT datasets. AI

IMPACT This research introduces a new method for creating detailed digital twins of cerebral perfusion, potentially improving diagnostic accuracy for conditions like acute stroke.

RANK_REASON The cluster describes a new research paper detailing a novel system for medical imaging analysis. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.CV →

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DuoPIC system creates uncertainty-aware digital twins of cerebral perfusion

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The cluster describes a new research paper detailing a novel system for medical imaging analysis. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Anh Duong Tran, Quang-Anh N. D., Toan Sy Pham, Trang H. Hoang, Minh N. Do, Duy Ton Mai, Huan X. Nguyen ·

    DuoPIC: Uncertainty-Aware Voxel-Level Digital Twins of Cerebral Perfusion with Transport PDEs in Acute Stroke

    arXiv:2610.33071v1 Announce Type: new Abstract: Digital twins of cerebral perfusion relate tracer dynamics to cerebral blood flow (CBF), blood volume (CBV) and mean transit time (MTT), but must be data-driven, physically consistent and uncertainty-aware. We introduce DuoPIC, a di…