A survey on U-shaped networks in medical image segmentations
The U-shaped network is one of the end-to-end convolutional neural networks (CNNs). In
electron microscope segmentation of ISBI challenge 2012, the concise architecture and …
electron microscope segmentation of ISBI challenge 2012, the concise architecture and …
Automatic detection of white matter hyperintensities in healthy aging and pathology using magnetic resonance imaging: a review
ME Caligiuri, P Perrotta, A Augimeri, F Rocca… - Neuroinformatics, 2015 - Springer
White matter hyperintensities (WMH) are commonly seen in the brain of healthy elderly
subjects and patients with several neurological and vascular disorders. A truly reliable and …
subjects and patients with several neurological and vascular disorders. A truly reliable and …
[HTML][HTML] BIANCA (Brain Intensity AbNormality Classification Algorithm): A new tool for automated segmentation of white matter hyperintensities
Reliable quantification of white matter hyperintensities of presumed vascular origin (WMHs)
is increasingly needed, given the presence of these MRI findings in patients with several …
is increasingly needed, given the presence of these MRI findings in patients with several …
[HTML][HTML] White matter hyperintensity and stroke lesion segmentation and differentiation using convolutional neural networks
White matter hyperintensities (WMH) are a feature of sporadic small vessel disease also
frequently observed in magnetic resonance images (MRI) of healthy elderly subjects. The …
frequently observed in magnetic resonance images (MRI) of healthy elderly subjects. The …
Deep convolutional neural network for accurate segmentation and quantification of white matter hyperintensities
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 …
magnetic resonance imaging (MRI) images, that can be identified in MRI images of elderly …
Detection of subtle white matter lesions in MRI through texture feature extraction and boundary delineation using an embedded clustering strategy
White matter lesions (WML) underlie multiple brain disorders, and automatic WML
segmentation is crucial to evaluate the natural disease course and effectiveness of clinical …
segmentation is crucial to evaluate the natural disease course and effectiveness of clinical …
Application of variable threshold intensity to segmentation for white matter hyperintensities in fluid attenuated inversion recovery magnetic resonance images
BI Yoo, JJ Lee, JW Han, SYW Oh, EY Lee, JR MacFall… - Neuroradiology, 2014 - Springer
Abstract Introduction White matter hyperintensities (WMHs) are regions of abnormally high
intensity on T2-weighted or fluid-attenuated inversion recovery (FLAIR) magnetic resonance …
intensity on T2-weighted or fluid-attenuated inversion recovery (FLAIR) magnetic resonance …
A large margin algorithm for automated segmentation of white matter hyperintensity
Precise detection and quantification of white matter hyperintensity (WMH) is of great interest
in studies of neurological and vascular disorders. In this work, we propose a novel method …
in studies of neurological and vascular disorders. In this work, we propose a novel method …
A deep semantic segmentation correction network for multi-model tiny lesion areas detection
Background Semantic segmentation of white matter hyperintensities related to focal cerebral
ischemia (FCI) and lacunar infarction (LACI) is of significant importance for the automatic …
ischemia (FCI) and lacunar infarction (LACI) is of significant importance for the automatic …
[HTML][HTML] Multi-atlas based detection and localization (MADL) for location-dependent quantification of white matter hyperintensities
The extent and spatial location of white matter hyperintensities (WMH) on brain MRI may be
relevant to the development of cognitive decline in older persons. Here, we introduce a new …
relevant to the development of cognitive decline in older persons. Here, we introduce a new …