AIMC Topic: Magnetic Resonance Imaging

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Predicting primary progressive aphasias with support vector machine approaches in structural MRI data.

NeuroImage. Clinical
Primary progressive aphasia (PPA) encompasses the three subtypes nonfluent/agrammatic variant PPA, semantic variant PPA, and the logopenic variant PPA, which are characterized by distinct patterns of language difficulties and regional brain atrophy. ...

Deep ensemble learning of sparse regression models for brain disease diagnosis.

Medical image analysis
Recent studies on brain imaging analysis witnessed the core roles of machine learning techniques in computer-assisted intervention for brain disease diagnosis. Of various machine-learning techniques, sparse regression models have proved their effecti...

Predicting prostate tumour location from multiparametric MRI using Gaussian kernel support vector machines: a preliminary study.

Australasian physical & engineering sciences in medicine
The performance of a support vector machine (SVM) algorithm was investigated to predict prostate tumour location using multi-parametric MRI (mpMRI) data. The purpose was to obtain information of prostate tumour location for the implementation of bio-...

A fuzzy integral method based on the ensemble of neural networks to analyze fMRI data for cognitive state classification across multiple subjects.

Journal of integrative neuroscience
The huge number of voxels in fMRI over time poses a major challenge to for effective analysis. Fast, accurate, and reliable classifiers are required for estimating the decoding accuracy of brain activities. Although machine-learning classifiers seem ...

The Default Mode Network in Healthy Individuals: A Systematic Review and Meta-Analysis.

Brain connectivity
When the brain is not engaged in goal-directed activities and at rest, there are still measureable patterns of activity. One resting-state network, the default mode network (DMN) is responsible for a self-referential introspective state. There are ma...

Learning MRI-based classification models for MGMT methylation status prediction in glioblastoma.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The O-methylguanine-DNA-methyltransferase (MGMT) promoter methylation has been shown to be associated with improved outcomes in patients with glioblastoma (GBM) and may be a predictive marker of sensitivity to chemotherapy. ...

An advanced MRI and MRSI data fusion scheme for enhancing unsupervised brain tumor differentiation.

Computers in biology and medicine
Proton Magnetic Resonance Spectroscopic Imaging (H MRSI) has shown great potential in tumor diagnosis since it provides localized biochemical information discriminating different tissue types, though it typically has low spatial resolution. Magnetic ...