AIMC Topic: Magnetic Resonance Imaging

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MR Image Super-Resolution via Wide Residual Networks With Fixed Skip Connection.

IEEE journal of biomedical and health informatics
Spatial resolution is a critical imaging parameter in magnetic resonance imaging. The image super-resolution (SR) is an effective and cost efficient alternative technique to improve the spatial resolution of MR images. Over the past several years, th...

MR-Only Brain Radiation Therapy: Dosimetric Evaluation of Synthetic CTs Generated by a Dilated Convolutional Neural Network.

International journal of radiation oncology, biology, physics
PURPOSE: This work aims to facilitate a fast magnetic resonance (MR)-only workflow for radiation therapy of intracranial tumors. Here, we evaluate whether synthetic computed tomography (sCT) images generated with a dilated convolutional neural networ...

The effect of machine learning regression algorithms and sample size on individualized behavioral prediction with functional connectivity features.

NeuroImage
Individualized behavioral/cognitive prediction using machine learning (ML) regression approaches is becoming increasingly applied. The specific ML regression algorithm and sample size are two key factors that non-trivially influence prediction accura...

Ischemic stroke lesion segmentation using stacked sparse autoencoder.

Computers in biology and medicine
Automatic segmentation of ischemic stroke lesion volumes from multi-spectral Magnetic Resonance Imaging (MRI) sequences plays a vital role in quantifying and locating the lesion region. Most existing methods mainly rely on designing hand-crafted feat...

DeepIGeoS: A Deep Interactive Geodesic Framework for Medical Image Segmentation.

IEEE transactions on pattern analysis and machine intelligence
Accurate medical image segmentation is essential for diagnosis, surgical planning and many other applications. Convolutional Neural Networks (CNNs) have become the state-of-the-art automatic segmentation methods. However, fully automatic results may ...

A deep learning approach for real time prostate segmentation in freehand ultrasound guided biopsy.

Medical image analysis
Targeted prostate biopsy, incorporating multi-parametric magnetic resonance imaging (mp-MRI) and its registration with ultrasound, is currently the state-of-the-art in prostate cancer diagnosis. The registration process in most targeted biopsy system...

Assessment of the Diagnostic Accuracy of Biparametric Magnetic Resonance Imaging for Prostate Cancer in Biopsy-Naive Men: The Biparametric MRI for Detection of Prostate Cancer (BIDOC) Study.

JAMA network open
IMPORTANCE: Multiparametric magnetic resonance imaging (MRI) enhances detection and risk stratification for significant prostate cancer but is time-consuming (approximately 40 minutes) and expensive. Rapid and simpler (approximately 15-minute) bipara...

Structural brain changes versus self-report: machine-learning classification of chronic fatigue syndrome patients.

Experimental brain research
Chronic fatigue syndrome (CFS) is a disorder associated with fatigue, pain, and structural/functional abnormalities seen during magnetic resonance brain imaging (MRI). Therefore, we evaluated the performance of structural MRI (sMRI) abnormalities in ...

Volumetric brain magnetic resonance imaging predicts functioning in bipolar disorder: A machine learning approach.

Journal of psychiatric research
Neuroimaging studies have been steadily explored in Bipolar Disorder (BD) in the last decades. Neuroanatomical changes tend to be more pronounced in patients with repeated episodes. Although the role of such changes in cognition and memory is well es...