Mri Analysis
Mri Analysis - Related Videos
06:21
In Vivo MRI Analysis of Cranial Nerve Morphology in a Patient with Inner Ear Disorder
0 Views •
2025
Source: Flatz, W. H. et al. In Vivo Morphometric Analysis of Human Cranial Nerves Using Magnetic Resonance Imaging in Menière's Disease Ears and Normal Hearing Ears. J. Vis. Exp. (2018).This video demonstrates the use of MRI to analyze cranial nerve morphology in the ears of patients suffering from a chronic inner ear disorder. It outlines the steps for performing a high magnetic field MRI scan on the patient, reconstructing the high-resolution 3D cross-sectional images of the cranial nerves,...
06:06
Optogenetic Functional MRI
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Cited by 15 •
2016
This protocol describes the steps and data analysis required to successfully perform optogenetic functional magnetic resonance imaging (ofMRI). ofMRI is a novel technique that combines high-field fMRI readout with optogenetic stimulation, allowing for cell type-specific mapping of functional neural circuits and their dynamics across the whole living brain.
12:09
Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
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Cited by 35 •
2014
The Default Mode Network (DMN) in Temporal Lobe Epilepsy (TLE) is analyzed in the resting state of the brain using seed-based functional connectivity MRI (fcMRI).
06:58
Synthesis of an In vivo MRI-detectable Apoptosis Probe
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Cited by 3 •
2012
Early detection of apoptosis may identify at-risk cell populations in a variety of diseases. Here we demonstrate a method to link an early apoptosis-detection protein (Annexin V) to a MRI-detectable iron oxide nanoparticle (SPIO). This method may be extended to other proteins of interest to generate MRI-detectable molecular imaging probes.
08:20
MRI-guided dmPFC-rTMS as a Treatment for Treatment-resistant Major Depressive Disorder
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Cited by 31 •
2015
Here we outline the procedure for MRI-guided repetitive transcranial magnetic stimulation to the dorsomedial prefrontal cortex as an experimental treatment for major depressive disorder.
FAQs
MRI analysis distinguishes tissues by comparing signal intensity, contrast, and spatial distribution across an image. These patterns help identify boundaries and differences between anatomical structures or abnormal regions. Interpreting all three features together is important because a region may be clinically meaningful not only because it appears brighter or darker, but because its signal pattern and location differ from surrounding tissue.
Image segmentation divides an image into regions that can correspond to anatomical structures or areas of disease. This makes it possible to calculate measurements rather than rely only on visual impressions. In practice, segmentation can support assessment of size, spatial distribution, or change over time, helping reveal subtle findings and support comparisons across examinations.
Longitudinal comparisons examine images from different time points to identify changes in anatomy, tissue properties, or disease-related regions. When paired with quantitative measurements, they can show whether an observed feature is stable, changing, or newly apparent. This supports disease monitoring and helps inform treatment planning and clinical decisions.
A practical workflow begins by reviewing signal intensity, contrast, and spatial distribution, then locating the anatomy or abnormal region relevant to the clinical question. The analyst may segment selected structures, record quantitative measurements, and compare results with earlier images when available. This sequence connects image interpretation with measurable evidence for diagnosis, treatment planning, or monitoring.
The method can be applied to the brain, spine, joints, organs, tumors, and vascular structures. In each setting, analysis helps characterize anatomy and disease-related findings, while measurements and image comparisons can support diagnosis, treatment planning, or monitoring. The relevant target depends on the clinical question and the structures visible in the images.
Findings gain meaning from their anatomical location, signal pattern, contrast, and distribution rather than from intensity alone. Reviewing these features alongside segmentation, measurements, and prior images can clarify whether a difference represents a stable feature or a meaningful change. This integrated review informs diagnosis, treatment planning, and disease monitoring in clinical practice.