A review on brain tumor segmentation of MRI images
The process of segmenting tumor from MRI image of a brain is one of the highly focused
areas in the community of medical science as MRI is noninvasive imaging. This paper …
areas in the community of medical science as MRI is noninvasive imaging. This paper …
Survey of automated multiple sclerosis lesion segmentation techniques on magnetic resonance imaging
A Danelakis, T Theoharis, DA Verganelakis - … Medical Imaging and …, 2018 - Elsevier
Multiple sclerosis (MS) is a chronic disease. It affects the central nervous system and its
clinical manifestation can variate. Magnetic Resonance Imaging (MRI) is often used to …
clinical manifestation can variate. Magnetic Resonance Imaging (MRI) is often used to …
Improving automated multiple sclerosis lesion segmentation with a cascaded 3D convolutional neural network approach
In this paper, we present a novel automated method for White Matter (WM) lesion
segmentation of Multiple Sclerosis (MS) patient images. Our approach is based on a …
segmentation of Multiple Sclerosis (MS) patient images. Our approach is based on a …
Predicting cognitive decline in multiple sclerosis: a 5-year follow-up study
AJC Eijlers, Q van Geest, I Dekker, MD Steenwijk… - Brain, 2018 - academic.oup.com
Cognitive decline is common in multiple sclerosis and strongly affects overall quality of life.
Despite the identification of cross-sectional MRI correlates of cognitive impairment …
Despite the identification of cross-sectional MRI correlates of cognitive impairment …
[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 …
Cortical atrophy patterns in multiple sclerosis are non-random and clinically relevant
Abstract See Chard and Miller (doi: 10.1093/brain/awv354) for a scientific commentary on
this article. Grey matter atrophy is common in multiple sclerosis. However, in contrast with …
this article. Grey matter atrophy is common in multiple sclerosis. However, in contrast with …
Brain tumour classification using two‐tier classifier with adaptive segmentation technique
V Anitha, S Murugavalli - IET computer vision, 2016 - Wiley Online Library
A brain tumour is a mass of tissue that is structured by a gradual addition of anomalous cells
and it is important to classify brain tumours from the magnetic resonance imaging (MRI) for …
and it is important to classify brain tumours from the magnetic resonance imaging (MRI) for …
[HTML][HTML] Automatic segmentation and volumetry of multiple sclerosis brain lesions from MR images
The location and extent of white matter lesions on magnetic resonance imaging (MRI) are
important criteria for diagnosis, follow-up and prognosis of multiple sclerosis (MS). Clinical …
important criteria for diagnosis, follow-up and prognosis of multiple sclerosis (MS). Clinical …
Attention convolutional neural network for accurate segmentation and quantification of lesions in ischemic stroke disease
Ischemic stroke lesion and white matter hyperintensity (WMH) lesion appear as regions of
abnormally signal intensity on magnetic resonance image (MRI) sequences. Ischemic stroke …
abnormally signal intensity on magnetic resonance image (MRI) sequences. Ischemic stroke …
A novel negative-transfer-resistant fuzzy clustering model with a shared cross-domain transfer latent space and its application to brain CT image segmentation
Traditional clustering algorithms for medical image segmentation can only achieve
satisfactory clustering performance under relatively ideal conditions, in which there is …
satisfactory clustering performance under relatively ideal conditions, in which there is …