AIMC Topic: Magnetic Resonance Imaging

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Automated assessment of thigh composition using machine learning for Dixon magnetic resonance images.

Magma (New York, N.Y.)
OBJECTIVES: To develop and validate a machine learning based automated segmentation method that jointly analyzes the four contrasts provided by Dixon MRI technique for improved thigh composition segmentation accuracy.

Automatic Segmentation of MR Brain Images With a Convolutional Neural Network.

IEEE transactions on medical imaging
Automatic segmentation in MR brain images is important for quantitative analysis in large-scale studies with images acquired at all ages. This paper presents a method for the automatic segmentation of MR brain images into a number of tissue classes u...

The effect of preprocessing pipelines in subject classification and detection of abnormal resting state functional network connectivity using group ICA.

NeuroImage
Resting state functional network connectivity (rsFNC) derived from functional magnetic resonance (fMRI) imaging is emerging as a possible biomarker to identify several brain disorders. Recently it has been pointed out that methods used to preprocess ...

Machine Learning Classification of Cirrhotic Patients with and without Minimal Hepatic Encephalopathy Based on Regional Homogeneity of Intrinsic Brain Activity.

PloS one
Machine learning-based approaches play an important role in examining functional magnetic resonance imaging (fMRI) data in a multivariate manner and extracting features predictive of group membership. This study was performed to assess the potential ...

Voxel-Based Diagnosis of Alzheimer's Disease Using Classifier Ensembles.

IEEE journal of biomedical and health informatics
Functional magnetic resonance imaging (fMRI) is one of the most promising noninvasive techniques for early Alzheimer's disease (AD) diagnosis. In this paper, we explore the application of different machine learning techniques to the classification of...

Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images.

IEEE transactions on medical imaging
Among brain tumors, gliomas are the most common and aggressive, leading to a very short life expectancy in their highest grade. Thus, treatment planning is a key stage to improve the quality of life of oncological patients. Magnetic resonance imaging...

Preconditioning 2D Integer Data for Fast Convex Hull Computations.

PloS one
In order to accelerate computing the convex hull on a set of n points, a heuristic procedure is often applied to reduce the number of points to a set of s points, s ≤ n, which also contains the same hull. We present an algorithm to precondition 2D da...

Clinical impact of prostate biopsy undergrading in an academic and community setting.

World journal of urology
PURPOSE: To evaluate whether the rate of Gleason score (GS) upgrade on final pathology, the rate of positive surgical margins (PSM) and the rate of biochemical recurrence (BCR) after radical prostatectomy (RP) were different if prostate biopsy (PB) w...

Accelerated Brain Aging in Schizophrenia: A Longitudinal Pattern Recognition Study.

The American journal of psychiatry
OBJECTIVE: Despite the multitude of longitudinal neuroimaging studies that have been published, a basic question on the progressive brain loss in schizophrenia remains unaddressed: Does it reflect accelerated aging of the brain, or is it caused by a ...

HYDRA: Revealing heterogeneity of imaging and genetic patterns through a multiple max-margin discriminative analysis framework.

NeuroImage
Multivariate pattern analysis techniques have been increasingly used over the past decade to derive highly sensitive and specific biomarkers of diseases on an individual basis. The driving assumption behind the vast majority of the existing methodolo...