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Diffusion Tensor Imaging

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Predicting Prodromal Alzheimer's Disease in Subjects with Mild Cognitive Impairment Using Machine Learning Classification of Multimodal Multicenter Diffusion-Tensor and Magnetic Resonance Imaging Data.

Journal of neuroimaging : official journal of the American Society of Neuroimaging
BACKGROUND: Alzheimer's disease (AD) patients show early changes in white matter (WM) structural integrity. We studied the use of diffusion tensor imaging (DTI) in assessing WM alterations in the predementia stage of mild cognitive impairment (MCI).

Detection of temporal lobe epilepsy using support vector machines in multi-parametric quantitative MR imaging.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The detection of MRI abnormalities that can be associated to seizures in the study of temporal lobe epilepsy (TLE) is a challenging task. In many cases, patients with a record of epileptic activity do not present any discernible MRI findings. In this...

TractCloud-FOV: Deep Learning-Based Robust Tractography Parcellation in Diffusion MRI With Incomplete Field of View.

Human brain mapping
Tractography parcellation classifies streamlines reconstructed from diffusion MRI into anatomically defined fiber tracts for clinical and research applications. However, clinical scans often have incomplete fields of view (FOV) where brain regions ar...

The Shape of the Brain's Connections Is Predictive of Cognitive Performance: An Explainable Machine Learning Study.

Human brain mapping
The shape of the brain's white matter connections is relatively unexplored in diffusion magnetic resonance imaging (dMRI) tractography analysis. While it is known that tract shape varies in populations and across the human lifespan, it is unknown if ...

Tractography-Based Automated Identification of Retinogeniculate Visual Pathway With Novel Microstructure-Informed Supervised Contrastive Learning.

Human brain mapping
The retinogeniculate visual pathway (RGVP) is responsible for carrying visual information from the retina to the lateral geniculate nucleus. Identification and visualization of the RGVP are important in studying the anatomy of the visual system and c...

Deep multimodal saliency parcellation of cerebellar pathways: Linking microstructure and individual function through explainable multitask learning.

Human brain mapping
Parcellation of human cerebellar pathways is essential for advancing our understanding of the human brain. Existing diffusion magnetic resonance imaging tractography parcellation methods have been successful in defining major cerebellar fibre tracts,...

Interhemispheric connections in the maintenance of language performance and prognosis prediction: fully connected layer-based deep learning model analysis.

Neurosurgical focus
OBJECTIVE: Language-related networks have been recognized in functional maintenance, which has also been considered the mechanism of plasticity and reorganization in patients with cerebral malignant tumors. However, the role of interhemispheric conne...

[Clinical study on application of 3D Slicer software assisted domestic frameless stereotactic robot in biopsy of intracranial lesions].

Zhonghua wai ke za zhi [Chinese journal of surgery]
To examine the application value of 3D Slicer software assisted domestic frameless stereotactic robot in biopsy of intracranial lesions. A retrospective analysis was performed on 80 patients who admitted consecutively and underwent intracerebral le...

Input Agnostic Deep Learning for Alzheimer's Disease Classification Using Multimodal MRI Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Alzheimer's disease (AD) is a progressive brain disorder that causes memory and functional impairments. The advances in machine learning and publicly available medical datasets initiated multiple studies in AD diagnosis. In this work, we utilize a mu...

Automatic Volumetric Quality Assessment of Diffusion MR Images via Convolutional Neural Network Classifiers.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Diffusion Tensor Imaging (DTI) is widely used to find brain biomarkers for various stages of brain structural and neuronal development. Processing DTI data requires a detailed Quality Assessment (QA) to detect artifactual volumes amongst a large pool...