Isotropic Voxels
Isotropic Voxels - Related Videos
09:17
Measuring Grey Matter Differences with Voxel-based Morphometry: The Musical Brain
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2023
Source: Laboratories of Jonas T. Kaplan and Sarah I. Gimbel—University of Southern California Experience shapes the brain. It is well understood that our brains are different as a result of learning. While many experience-related changes manifest themselves at the microscopic level, for example by neurochemical adjustments in the behavior of individual neurons, we may also examine anatomical changes to the structure of the brain at a macroscopic level. One famous example of this kind of change...
07:12
Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
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Cited by 23 •
2014
Informational connectivity measures the correspondence between time courses of multi-voxel information across different brain regions. Multi-voxel pattern discriminability time series are extracted from regions and compared, revealing networks that are not identified in a typical functional connectivity approach.
09:11
Nanoscopic Imaging of Human Tissue Sections via Physical and Isotropic Expansion
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Cited by 5 •
2019
Nanoscale imaging of clinical tissue samples can improve understanding of disease pathogenesis. Expansion pathology (ExPath) is a version of expansion microscopy (ExM), modified for compatibility with standard clinical tissue samples, to explore the nanoscale configuration of biomolecules using conventional diffraction limited microscopes.
12:08
From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
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Cited by 14 •
2014
The bottleneck for cellular 3D electron microscopy is feature extraction (segmentation) in highly complex 3D density maps. We have developed a set of criteria, which provides guidance regarding which segmentation approach (manual, semi-automated, or automated) is best suited for different data types, thus providing a starting point for effective segmentation.
11:36
Voxel Printing Anatomy: Design and Fabrication of Realistic, Presurgical Planning Models through Bitmap Printing
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Cited by 1 •
2022
This method demonstrates a voxel-based 3D printing workflow, which prints directly from medical images with exact spatial fidelity and spatial/contrast resolution. This enables the precise, graduated control of material distributions through morphologically complex, graduated materials correlated to radiodensity without loss or alteration of data.
FAQs
Equal spatial sampling across the three axes makes measurements more comparable when a brain structure is examined in different orientations. A structure should not appear to have a different scale simply because it is viewed along another axis. In neuroscience, this supports more consistent assessment of anatomy and strengthens interpretation of volumetric MRI or other three-dimensional imaging data.
They allow a volumetric dataset to be reformatted into axial, sagittal, or coronal views while preserving consistent spatial relationships. This is especially useful when a structure or abnormality is easier to inspect from an orientation different from the original acquisition. Researchers can therefore examine three-dimensional neural anatomy without introducing direction-dependent distortion into the displayed geometry.
Registration aligns images acquired at different times, or from different sources, so corresponding anatomy can be compared. Isotropic voxel data provide standardized spatial units for this alignment, helping preserve comparable geometry across the volume. That consistency supports analyses involving brain-structure visualization, longitudinal comparisons, and integration of scans within broader neuroimaging workflows.
They are produced either during image acquisition or through reconstruction of the acquired data. The relevant processing goal is to make voxel width, height, and depth match across the x, y, and z axes. Once generated, the resulting volume can support consistent reformatting, registration, anatomical measurement, and computational analysis in three dimensions.
They are particularly useful when measurements depend on the shape, extent, or position of a cortical feature or lesion in three dimensions. Equal spatial resolution helps reduce directional differences when the feature is inspected or measured from multiple planes. This can improve visualization and support more consistent quantitative comparisons across neuroimaging datasets.
These analyses require volumetric data that can be processed consistently throughout the brain. Isotropic voxels provide standardized inputs for identifying structures during segmentation, representing neural pathways during tractography, and reconstructing anatomy in three-dimensional maps. Their uniform spatial sampling helps computational workflows operate on comparable geometry rather than data whose resolution changes with viewing direction.