Automated algorithm for counting microbleeds in patients with familial cerebral cavernous malformations

Purpose Familial cerebral cavernous malformation (CCM) patients present with multiple lesions that can grow both in number and size over time and are reliably detected on susceptibility-weighted imaging (SWI). Manual counting of lesions is arduous and subject to high variability. We aimed to develop...

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Vydáno v:	Neuroradiology Ročník 59; číslo 7; s. 685 - 690
Hlavní autoři:	Zou, Xiaowei, Hart, Blaine L., Mabray, Marc, Bartlett, Mary R., Bian, Wei, Nelson, Jeffrey, Morrison, Leslie A., McCulloch, Charles E., Hess, Christopher P., Lupo, Janine M., Kim, Helen
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin/Heidelberg Springer Berlin Heidelberg 01.07.2017 Springer Nature B.V
Témata:	Algorithms Automation Brain Brain cancer Brain tumors Cerebral Hemorrhage - diagnostic imaging Congenital defects Counting Female Functional Neuroradiology Hemangioma, Cavernous, Central Nervous System - diagnostic imaging Hemorrhage Humans Image Interpretation, Computer-Assisted - methods Imaging Lesions Magnetic Resonance Imaging - methods Male Medicine Medicine & Public Health Middle Aged Neuroimaging Neurology Neuroradiology Neurosciences Neurosurgery Patients Radiation Radiation effects Radiology Regression analysis Risk Factors Robustness (mathematics) Sensitivity Sensitivity analysis Vein & artery diseases Susceptibility-weighted imaging Cerebral cavernous malformations Automated lesion counting Microbleeds
ISSN:	0028-3940, 1432-1920, 1432-1920
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