Decoding pulsatile patterns of cerebrospinal fluid dynamics through enhancing interpretability in machine learning

Abstract Analyses of complex behaviors of Cerebrospinal Fluid (CSF) have become increasingly important in diseases diagnosis. The changes of the phase-contrast magnetic resonance imaging (PC-MRI) signal formed by the velocity of flowing CSF are represented as a set of velocity-encoded images or maps...

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Principais autores:	Ayse Keles, Pinar Akdemir Ozisik, Oktay Algin, Fatih Vehbi Celebi, Malika Bendechache
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Nature Portfolio 2024-08-01
coleção:	Scientific Reports
Assuntos:	Idiopathic scoliosis Cerebrospinal fluid CSF Pulsatile information PC-MRI Interpretable machine learning
Acesso em linha:	https://doi.org/10.1038/s41598-024-67928-4
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