AIMC Topic: Magnetic Resonance Imaging

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Deep learning-assisted preclinical MR fingerprinting for sub-millimeter T and T mapping of entire macaque brain.

Magnetic resonance in medicine
PURPOSE: Preclinical MR fingerprinting (MRF) suffers from long acquisition time for organ-level coverage due to demanding image resolution and limited undersampling capacity. This study aims to develop a deep learning-assisted fast MRF framework for ...

High-resolution spiral real-time cardiac cine imaging with deep learning-based rapid image reconstruction and quantification.

NMR in biomedicine
The objective of the current study was to develop and evaluate a DEep learning-based rapid Spiral Image REconstruction (DESIRE) and deep learning (DL)-based segmentation approach to quantify the left ventricular ejection fraction (LVEF) for high-reso...

Quantitative image signature and machine learning-based prediction of outcomes in cerebral cavernous malformations.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
PURPOSE: There is increasing interest in novel prognostic tools and predictive biomarkers to help identify, with more certainty, cerebral cavernous malformations (CCM) susceptible of bleeding if left untreated. We developed explainable quantitative-b...

A deep-learning approach for segmentation of liver tumors in magnetic resonance imaging using UNet+.

BMC cancer
OBJECTIVE: Radiomic and deep learning studies based on magnetic resonance imaging (MRI) of liver tumor are gradually increasing. Manual segmentation of normal hepatic tissue and tumor exhibits limitations.

Deep learning system for automated detection of posterior ligamentous complex injury in patients with thoracolumbar fracture on MRI.

Scientific reports
This study aimed to develop a deep learning (DL) algorithm for automated detection and localization of posterior ligamentous complex (PLC) injury in patients with acute thoracolumbar (TL) fracture on magnetic resonance imaging (MRI) and evaluate its ...

Deep Learning-Based Ensembling Technique to Classify Alzheimer's Disease Stages Using Functional MRI.

Journal of healthcare engineering
The major issue faced by elderly people in society is the loss of memory, difficulty learning new things, and poor judgment. This is due to damage to brain tissues, which may lead to cognitive impairment and eventually Alzheimer's. Therefore, the det...

Optimized 3D brachial plexus MR neurography using deep learning reconstruction.

Skeletal radiology
OBJECTIVE: To evaluate whether 'fast,' unilateral, brachial plexus, 3D magnetic resonance neurography (MRN) acquisitions with deep learning reconstruction (DLR) provide similar image quality to longer, 'standard' scans without DLR.

Human lower leg muscles grow asynchronously.

Journal of anatomy
Muscle volume must increase substantially during childhood growth to generate the power required to propel the growing body. One unresolved but fundamental question about childhood muscle growth is whether muscles grow at equal rates; that is, if mus...

Research related to the diagnosis of prostate cancer based on machine learning medical images: A review.

International journal of medical informatics
BACKGROUND: Prostate cancer is currently the second most prevalent cancer among men. Accurate diagnosis of prostate cancer can provide effective treatment for patients and greatly reduce mortality. The current medical imaging tools for screening pros...