Performance testing of a novel deep learning algorithm for the detection of intracranial hemorrhage and first trial under clinical conditions

Purpose: We evaluate the performance of a deep learning-based pipeline using a Dense U-net architecture for detection of intracranial hemorrhage (ICH) in unenhanced head computed tomography (CT) scans. Methods: A balanced database was assembled retrospectively, comprising a total of 872 CT scans (36...

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Autores principales: Philipp Gruschwitz, Jan-Peter Grunz, Philipp Josef Kuhl, Aleksander Kosmala, Thorsten Alexander Bley, Bernhard Petritsch, Julius Frederik Heidenreich
Formato: article
Lenguaje:EN
Publicado: Elsevier 2021
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Acceso en línea:https://doaj.org/article/f1cda05677124302bb057aff68cffea7
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