3d Surface Imaging
3d Surface Imaging - Related Videos
09:41
A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery
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Cited by 19 •
2016
We describe the steps to use our custom designed software for image integration, visualization and planning in epilepsy surgery.
08:06
Interview: Bioreactors and Surfaced-Modified 3D-Scaffolds for Stem Cell Research
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2008
In the past many in vitro culture systems -- mainly monolayer cultures -- often suffered from the disadvantage that differentiated primary cells had a relatively short life-span and de-differentiated during culture. As a consequence, most of their organ-specific functions were lost rapidly. Thus, in order to reproduce better conditions for these cells in vitro, modifications and adaptations have been made to conventional monolayer cultures.
04:36
Real-Time Imaging of Bonding in 3D-Printed Layers
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Cited by 2 •
2023
With a non-invasive and real-time technique, nanoscopic polymer motion inside a polymer filament is imaged during 3D printing. Fine-tuning this motion is crucial for producing constructs with optimal performance and appearance. This method reaches the core of plastic layer fusion, thus offering insights into optimal printing conditions and material design criteria.
11:59
High-speed Particle Image Velocimetry Near Surfaces
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Cited by 19 •
2013
A procedure for studying transient flows near boundaries using high-resolution, high-speed particle image velocimetry (PIV) is described here. PIV is a non-intrusive measurement technique applicable to any optically accessible flow by optimizing several parameter constraints such as the image and recording properties, the laser sheet properties, and analysis algorithms.
07:27
Rapid Acquisition of 3D Images Using High-resolution Episcopic Microscopy
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Cited by 2 •
2016
We describe a detailed protocol using high-resolution episcopic microscopy to acquire three-dimensional (3D) images of mouse embryos. This improved protocol utilizes a modified tissue preparation method to enhance penetration of the fluorescent dye, thereby permitting morphometric analysis of both small and large-sized specimens.
FAQs
Multiple viewpoints provide depth measurements from different spatial perspectives, while structured light supplies scan-based information about surface geometry. Computational reconstruction combines these measurements into a coherent model and can add texture to the resulting surface representation. In neuroscience, this workflow helps preserve the spatial arrangement of cortical folds, exposed tissue, or other anatomical features for later visualization and analysis.
A single 2D image does not directly show the full geometry of a surface, including how regions curve or relate spatially across depth. Three-dimensional models make surface area, curvature, and spatial relationships available for inspection and quantitative analysis. This added geometric information supports more detailed comparisons of anatomy and helps document structural changes that may be difficult to interpret in two dimensions.
Researchers can examine cortical folds, exposed brain tissue, neural structures, and experimental specimens as three-dimensional surfaces. The reconstructed models support both visual assessment and measurements of geometric properties such as surface area and curvature. These features provide structural context for comparing specimens or anatomical conditions and for relating visible surface organization to other neuroimaging observations.
A typical workflow records the target surface from multiple viewpoints or scans it with structured light. The system then derives depth measurements and applies computational reconstruction to assemble those data into a three-dimensional representation. Texture may be incorporated into the model, producing a spatially interpretable record that can be visualized, measured, compared, or integrated with other structural observations.
Researchers may use the technique to compare anatomy across specimens, developmental stages, or disease-related conditions. Because the models preserve surface area, curvature, and spatial relationships, they provide a basis for documenting how visible structure differs between observations. The same information can also support procedure guidance when researchers or clinicians need a clearer spatial record of exposed or accessible brain tissue.
Three-dimensional surface models can be integrated with other neuroimaging data to connect detailed surface geometry with broader structural observations. In neuroscience, this combination helps place cortical folds, neural structures, or exposed tissue within a richer spatial context. The result is not limited to visualization: researchers can use the combined information to compare anatomy and interpret surface measurements alongside complementary imaging findings.