3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study
This study investigates a 3D and fully convolutional neural network (CNN) for subcortical
brain structure segmentation in MRI. 3D CNN architectures have been generally avoided …
brain structure segmentation in MRI. 3D CNN architectures have been generally avoided …
Mindboggling morphometry of human brains
Mindboggle (http://mindboggle. info) is an open source brain morphometry platform that
takes in preprocessed T1-weighted MRI data and outputs volume, surface, and tabular data …
takes in preprocessed T1-weighted MRI data and outputs volume, surface, and tabular data …
MR Imaging of Human Brain Mechanics In Vivo: New Measurements to Facilitate the Development of Computational Models of Brain Injury
Computational models of the brain and its biomechanical response to skull accelerations
are important tools for understanding and predicting traumatic brain injuries (TBIs) …
are important tools for understanding and predicting traumatic brain injuries (TBIs) …
DeepHarmony: A deep learning approach to contrast harmonization across scanner changes
Magnetic resonance imaging (MRI) is a flexible medical imaging modality that often lacks
reproducibility between protocols and scanners. It has been shown that even when care is …
reproducibility between protocols and scanners. It has been shown that even when care is …
Evaluating white matter lesion segmentations with refined Sørensen-Dice analysis
The Sørensen-Dice index (SDI) is a widely used measure for evaluating medical image
segmentation algorithms. It offers a standardized measure of segmentation accuracy which …
segmentation algorithms. It offers a standardized measure of segmentation accuracy which …
Smart pathological brain detection by synthetic minority oversampling technique, extreme learning machine, and Jaya algorithm
YD Zhang, G Zhao, J Sun, X Wu, ZH Wang… - Multimedia Tools and …, 2018 - Springer
Pathological brain detection is an automated computer-aided diagnosis for brain images.
This study provides a novel method to achieve this goal. We first used synthetic minority …
This study provides a novel method to achieve this goal. We first used synthetic minority …
Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images
The human cerebellum plays an essential role in motor control, is involved in cognitive
function (ie, attention, working memory, and language), and helps to regulate emotional …
function (ie, attention, working memory, and language), and helps to regulate emotional …
Brain and retinal atrophy in African-Americans versus Caucasian-Americans with multiple sclerosis: a longitudinal study
Abstract On average, African Americans with multiple sclerosis demonstrate higher
inflammatory disease activity, faster disability accumulation, greater visual dysfunction, more …
inflammatory disease activity, faster disability accumulation, greater visual dysfunction, more …
Presurgical temporal lobe epilepsy connectome fingerprint for seizure outcome prediction
Temporal lobe epilepsy presents a unique situation where confident clinical localization of
the seizure focus does not always result in a seizure-free or favourable outcome after mesial …
the seizure focus does not always result in a seizure-free or favourable outcome after mesial …
Automatic segmentation of the thalamus using a massively trained 3D convolutional neural network: higher sensitivity for the detection of reduced thalamus volume by …
Objectives To develop an automatic method for accurate and robust thalamus segmentation
in T1w-MRI for widespread clinical use without the need for strict harmonization of …
in T1w-MRI for widespread clinical use without the need for strict harmonization of …