AIMC Topic: Gray Matter
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SVM recursive feature elimination analyses of structural brain MRI predicts near-term relapses in patients with clinically isolated syndromes suggestive of multiple sclerosis.
NeuroImage. Clinical
Oct 22, 2019
Machine learning classification is an attractive approach to automatically differentiate patients from healthy subjects, and to predict future disease outcomes. A clinically isolated syndrome (CIS) is often the first presentation of multiple sclerosi...
Unsupervised machine learning using an imaging mass spectrometry dataset automatically reassembles grey and white matter.
Scientific reports
Sep 13, 2019
Current histological and anatomical analysis techniques, including fluorescence in situ hybridisation, immunohistochemistry, immunofluorescence, immunoelectron microscopy and fluorescent fusion protein, have revealed great distribution diversity of m...
Using an artificial neural network for fast mapping of the oxygen extraction fraction with combined QSM and quantitative BOLD.
Magnetic resonance in medicine
Jul 4, 2019
PURPOSE: To apply an artificial neural network (ANN) for fast and robust quantification of the oxygen extraction fraction (OEF) from a combined QSM and quantitative BOLD analysis of gradient echo data and to compare the ANN to a traditional quasi-New...
Normal Distribution
Adult
Male
Image Processing, Computer-Assisted
Neural Networks, Computer
Oxygen Consumption
Humans
Magnetic Resonance Imaging
Brain Mapping
Healthy Volunteers
Brain
Least-Squares Analysis
Oxygen
Gray Matter
Computer Simulation
Positron-Emission Tomography
White Matter
Female
Cerebrovascular Circulation
Atrophy of cerebellar peduncles in essential tremor: a machine learning-based volumetric analysis.
European radiology
Jun 3, 2019
BACKGROUND: Subtle cerebellar signs are frequently observed in essential tremor (ET) and may be associated with cerebellar dysfunction. This study aims to evaluate the macrostructural integrity of the superior, middle, and inferior cerebellar peduncl...
Open-source pipeline for multi-class segmentation of the spinal cord with deep learning.
Magnetic resonance imaging
Apr 17, 2019
This paper presents an open-source pipeline to train neural networks to segment structures of interest from MRI data. The pipeline is tailored towards homogeneous datasets and requires relatively low amounts of manual segmentations (few dozen, or les...
Classification of radiologically isolated syndrome and clinically isolated syndrome with machine-learning techniques.
European journal of neurology
Mar 1, 2019
BACKGROUND AND PURPOSE: The unanticipated detection by magnetic resonance imaging (MRI) in the brain of asymptomatic subjects of white matter lesions suggestive of multiple sclerosis (MS) has been named radiologically isolated syndrome (RIS). As the ...
Automatic Tissue Image Segmentation Based on Image Processing and Deep Learning.
Journal of healthcare engineering
Jan 31, 2019
Image segmentation plays an important role in multimodality imaging, especially in fusion structural images offered by CT, MRI with functional images collected by optical technologies, or other novel imaging technologies. In addition, image segmentat...
Machine learning of brain gray matter differentiates sex in a large forensic sample.
Human brain mapping
Nov 15, 2018
Differences between males and females have been extensively documented in biological, psychological, and behavioral domains. Among these, sex differences in the rate and typology of antisocial behavior remains one of the most conspicuous and enduring...
Identifying a neuroanatomical signature of schizophrenia, reproducible across sites and stages, using machine learning with structured sparsity.
Acta psychiatrica Scandinavica
Sep 21, 2018
OBJECTIVE: Structural MRI (sMRI) increasingly offers insight into abnormalities inherent to schizophrenia. Previous machine learning applications suggest that individual classification is feasible and reliable and, however, is focused on the predicti...
Recognition of Schizophrenia with Regularized Support Vector Machine and Sequential Region of Interest Selection using Structural Magnetic Resonance Imaging.
Scientific reports
Sep 14, 2018
Structural brain abnormalities in schizophrenia have been well characterized with the application of univariate methods to magnetic resonance imaging (MRI) data. However, these traditional techniques lack sensitivity and predictive value at the indiv...
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