AIMC Topic: Magnetic Resonance Imaging
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Deep learning-based segmentation of the lung in MR-images acquired by a stack-of-spirals trajectory at ultra-short echo-times.
BMC medical imaging
May 8, 2021
BACKGROUND: Functional lung MRI techniques are usually associated with time-consuming post-processing, where manual lung segmentation represents the most cumbersome part. The aim of this study was to investigate whether deep learning-based segmentati...
Accelerated single-shot T2-weighted fat-suppressed (FS) MRI of the liver with deep learning-based image reconstruction: qualitative and quantitative comparison of image quality with conventional T2-weighted FS sequence.
European radiology
May 7, 2021
OBJECTIVE: To compare the image quality of an accelerated single-shot T2-weighted fat-suppressed (FS) MRI of the liver with deep learning-based image reconstruction (DL HASTE-FS) with conventional T2-weighted FS sequence (conventional T2 FS) at 1.5 T...
Feasibility of high-resolution magnetic resonance imaging of the liver using deep learning reconstruction based on the deep learning denoising technique.
Magnetic resonance imaging
May 7, 2021
PURPOSE: To evaluate the feasibility of High-resolution (HR) magnetic resonance imaging (MRI) of the liver using deep learning reconstruction (DLR) based on a deep learning denoising technique compared with standard-resolution (SR) imaging.
Artificial intelligence to predict task activation from resting state fMRI.
European radiology
May 7, 2021
Predicting Infarct Core From Computed Tomography Perfusion in Acute Ischemia With Machine Learning: Lessons From the ISLES Challenge.
Stroke
May 7, 2021
BACKGROUND AND PURPOSE: The ISLES challenge (Ischemic Stroke Lesion Segmentation) enables globally diverse teams to compete to develop advanced tools for stroke lesion analysis with machine learning. Detection of irreversibly damaged tissue on comput...
Altered Functional Connectivity of the Primary Visual Cortex in Patients With Iridocyclitis and Assessment of Its Predictive Value Using Machine Learning.
Frontiers in immunology
May 7, 2021
PURPOSE: To explore the intrinsic functional connectivity (FC) alteration of the primary visual cortex (V1) between individuals with iridocyclitis and healthy controls (HCs) by the resting-state functional magnetic resonance imaging (fMRI) technique,...
VolumeNet: A Lightweight Parallel Network for Super-Resolution of MR and CT Volumetric Data.
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
May 7, 2021
Deep learning-based super-resolution (SR) techniques have generally achieved excellent performance in the computer vision field. Recently, it has been proven that three-dimensional (3D) SR for medical volumetric data delivers better visual results th...
Development of a transperineal prostate biopsy robot guided by MRI-TRUS image.
The international journal of medical robotics + computer assisted surgery : MRCAS
May 6, 2021
BACKGROUND: In the transrectal ultrasound (TRUS)-guided transperineal prostate biopsy, doctors determine the biopsy target by observing the prostate region in TRUS images. However, ultrasound images with low imaging quality make doctors easy to be in...
Improving phase-based conductivity reconstruction by means of deep learning-based denoising of phase data for 3T MRI.
Magnetic resonance in medicine
May 5, 2021
PURPOSE: To denoise phase using a deep learning method for phase-based in vivo electrical conductivity reconstruction in a 3T MR system.
Artificial intelligence assists identifying malignant versus benign liver lesions using contrast-enhanced ultrasound.
Journal of gastroenterology and hepatology
May 5, 2021
BACKGROUND AND AIM: This study aims to construct a strategy that uses assistance from artificial intelligence (AI) to assist radiologists in the identification of malignant versus benign focal liver lesions (FLLs) using contrast-enhanced ultrasound (...
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