Multi-view Mri
Multi-view Mri - Related Videos
14:14
Quantification of Strain in a Porcine Model of Skin Expansion Using Multi-View Stereo and Isogeometric Kinematics
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Cited by 9 •
2017
This protocol uses multi-view stereo to generate three-dimensional (3D) models out of uncalibrated sequences of photographs, making it affordable and adjustable to a surgical setting. Strain maps between the 3D models are quantified with spline-based isogeometric kinematics, which facilitate representation of smooth surfaces over coarse meshes sharing the same parameterization.
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.
12:27
Noninvasive In Vivo Small Animal MRI and MRS: Basic Experimental Procedures
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Cited by 9 •
2009
This work describes basic procedures of noninvasive small animal MRI and MRS in vivo.
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.
01:29
Econometric Views (EViews)
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2025
Econometric Views, often stylized as EViews, is a package that merges statistical analysis with econometric studies. It is designed to provide tools for time series analysis, forecasting, and econometric model simulation. The software originated from MicroTSP software and has evolved significantly since its inception in 1981. The history of EViews is marked by a continuous effort to enhance its computational speed and user interface. It was initially developed for large computing systems but...
FAQs
Complementary views reduce uncertainty by showing the same biological region from different spatial perspectives. A feature that appears ambiguous in one plane can be evaluated against its position and shape in another, while additional contrasts may reveal differences in tissue appearance. In neuroscience, this broader spatial context helps distinguish normal anatomical variation from findings that merit closer analysis.
Alignment is essential because separately acquired images do not automatically provide a shared spatial reference. Registering the views allows corresponding structures to be compared and integrated rather than interpreted as unrelated pictures. This step supports coherent representation of brain anatomy and helps ensure that apparent differences reflect tissue or lesion characteristics, not simply changes in orientation.
Repeated acquisitions add complementary information rather than merely duplicating a single image. Different anatomical planes, orientations, or image contrasts can emphasize aspects of a structure that another acquisition leaves unclear. The resulting combination supports more complete assessment of regional tissue differences, which is particularly valuable when a single view cannot provide enough context for interpretation.
A Multi-view MRI workflow begins with acquiring images that provide complementary planes, orientations, or contrasts. The resulting datasets are then aligned so that corresponding anatomy shares a common spatial context, after which the views are integrated for examination or analysis. This sequence connects data collection with a more coherent representation of structures than isolated images can provide.
Researchers may choose this approach when brain anatomy, a lesion, or a regional tissue difference is difficult to interpret from one view. Comparing integrated perspectives can clarify spatial relationships and reduce ambiguity. In neuroscience, that makes the method relevant to image-based diagnosis as well as studies that examine how brain structure varies across regions.
The principal outcomes are improved visualization, stronger spatial context, and a basis for quantitative investigation. Integrated images can help investigators assess brain structures and lesions more comprehensively, while the combined information supports measurements of regional tissue differences. These outputs connect Multi-view MRI with both clinical image interpretation and neuroscience research on brain structure and disease.