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Deep convolutional neural network for accurate segmentation and quantification of white matter hyperintensities

Neurocomputing, 2020
Abstract White matter hyperintensities (WMHs) appear as regions of abnormally signal intensity on magnetic resonance imaging (MRI) images, that can be identified in MRI images of elderly people and ischemic stroke patients. However, manual segmentation and quantification of images with WMHs is laborious and time-consuming.
Liangliang Liu 0001   +5 more
openaire   +2 more sources

Association of deep white matter hyperintensity with left ventricular hypertrophy in acute ischemic stroke

Journal of Neuroimaging, 2021
AbstractBackground and PurposeWhite matter hyperintensities (WMHs) are associated with the presence of left ventricular hypertrophy (LVH). It is unclear if periventricular WMH (PV‐WMH) and or deep WMH (D‐WMH) are associated with LVH. We evaluated the association of PV‐WMH and D‐WMH with common transthoracic echocardiogram abnormalities, including LVH ...
Nandakumar Nagaraja   +2 more
openaire   +2 more sources

Different progression rates for deep white matter hyperintensities in elderly men and women

Neurology, 2004
The authors investigated the progression of white matter hyperintensities (WMHs) in a large population of elderly men and women. After 3 years of follow-up, women had accumulated approximately twice as much deep WMH (DWMH) as men. The progression of periventricular WMH was the same for men and women.
D M J, van den Heuvel   +9 more
openaire   +2 more sources

Deep-Learning-Based Segmentation and Localization of White Matter Hyperintensities on Magnetic Resonance Images

Interdisciplinary Sciences: Computational Life Sciences, 2020
White matter magnetic resonance hyperintensities of presumed vascular origin, which could be widely observed in elderly people, and has significant importance in multiple neurological studies. Quantitative measurement usually relies heavily on manual or semi-automatic delineation and intuitive localization, which is time-consuming and observer ...
Wenhao Jiang   +5 more
openaire   +2 more sources

Characterizing Deep White Matter Hyperintensities in Patients with Symptomatic Isolated Cortical Superficial Siderosis

Journal of Stroke and Cerebrovascular Diseases, 2017
In patient with cerebral amyloid angiopathy (CAA) presenting with lobar hemorrhage (LH), magnetic resonance imaging (MRI) white matter hyperintensities (WMH) tend to be predominant in posterior regions with the "multiple subcortical spots" WMH pattern as the most frequent topographical WMH pattern.
Renard, Dimitri   +5 more
openaire   +3 more sources

Relationship between interleukin‐6 and cerebral deep white matter and periventricular hyperintensity in elderly women

Geriatrics & Gerontology International, 2011
Aim:  We evaluated the relationships between serum levels of high‐sensitivity C‐reactive protein (hsCRP) and interleukin (IL)‐6 with the severity of leukoaraiosis.Methods:  One hundred and thirty‐seven elderly women who attended the Center for Comprehensive Care on Memory Disorders at Kyorin University Hospital were enrolled in this study ...
Kumiko, Nagai   +4 more
openaire   +2 more sources

Decline in Total Cerebral Blood Flow Is Linked with Increase in Periventricular but Not Deep White Matter Hyperintensities

Radiology, 2007
To retrospectively investigate the association between changes in total cerebral blood flow and progression of total, periventricular, and deep white matter hyperintensities over time.The institutional ethics review board approved the protocol for the prospective magnetic resonance (MR) imaging study, and all participants gave written informed consent.
V Hester, ten Dam   +7 more
openaire   +2 more sources

Development and validation of a deep learning-based automatic segmentation and classification of cerebral white matter hyperintensities

European Radiology
White matter hyperintensities (WMH) represent neuroimaging markers of cerebral small vessel disease. We aimed to develop and validate a deep learning-based simultaneous, automatic WMH segmentation and classification model in patients with cognitive impairment.This retrospective study included images from consecutive patients with cognitive impairment ...
So Yeong Jeong   +10 more
openaire   +2 more sources

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