Previous studies have reported abnormalities of white-matter diffusivity in pediatric bipolar disorder. However, it has not been established whether these abnormalities are able to distinguish individual subjects with pediatric bipolar disorder from ...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jul 21, 2015
The tongue is a critical organ for a variety of functions, including swallowing, respiration, and speech. It contains intrinsic and extrinsic muscles that play an important role in changing its shape and position. Diffusion tensor imaging (DTI) has b...
Many automatic segmentation methods are based on supervised machine learning. Such methods have proven to perform well, on the condition that they are trained on a sufficiently large manually labeled training set that is representative of the images ...
OBJECTIVE: The purpose of this study is to evaluate the ability of machine learning to discriminate between magnetic resonance images (MRI) of normal and pathological human articular cartilage obtained under standard clinical conditions.
Multimodality imaging is an emerging research topic in neuro-oncology for its potential of being able to demonstrate tumours in a more comprehensive manner. Diffusion-weighted magnetic resonance imaging (dMRI) and proton magnetic resonance spectrosco...
Multiparametric quantitative MRI based on multiple overlapping-echo detachment imaging (MQMOLED) can simultaneously quantify T and ADC with whole brain coverage within 40 s. T and ADC play an important role in the assessment and management of ischemi...
RATIONALE AND OBJECTIVES: This study aimed to develop and evaluate models for classifying the severity of neurological impairment in acute ischemic stroke (AIS) patients using multimodal MRI data.
RATIONALE AND OBJECTIVES: To develop and validate a deep learning system with guided diffusion-based data augmentation for grading partial-thickness supraspinatus tendon (SST) tears and to compare its performance with experienced radiologists, includ...
OBJECTIVES: This study aims to evaluate the feasibility and effectiveness of deep learning-based super-resolution techniques to reduce scan time while preserving image quality in high-resolution prostate diffusion-weighted imaging (DWI) with readout-...
PURPOSE: To develop a multiparametric breast MRI radiomics and deep learning-based multimodal model for predicting preoperative Ki-67 expression status in breast cancer, with the potential to advance individualized treatment and precision medicine fo...
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