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...

Full description

Saved in:

Bibliographic Details
Published in:	Neuroradiology Vol. 59; no. 7; pp. 685 - 690
Main Authors:	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
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01.07.2017 Springer Nature B.V
Subjects:	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
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!