Ct Scan Reconstruction
Ct Scan Reconstruction - Related Videos
05:27
FDG Based PET/CT Scan: A Method of Using Radiotracer for Non-invasive Imaging of Tumor Metabolism
0 Views •
2023
This article describes multimodality imaging of cancerous tissues with PET and CT diagnostic imaging by using a radiotracer 18F-FDG. Cancerous tissue with high glycolytic activity uptakes more 18F-FDG.
10:42
In Depth Analyses of LEDs by a Combination of X-ray Computed Tomography (CT) and Light Microscopy (LM) Correlated with Scanning Electron Microscopy (SEM)
0 Views •
Cited by 2 •
2016
A workflow for comprehensive micro-characterization of active optical devices is outlined. It contains structural as well as functional investigations by means of CT, LM and SEM. The method is demonstrated for a white LED which can be still be operated during characterization.
11:18
Micro-CT Imaging of a Mouse Spinal Cord
0 Views •
2023
Source: Peiman Shahbeigi-Roodposhti and Sina Shahbazmohamadi, Biomedical Engineering Department, University of Connecticut, Storrs, Connecticut It's a little-known fact that the discovery and (inadvertent) use of X-rays garnered the first ever Nobel Prize in Physics. The famous X-ray image of Dr. Röntgen's wife's hand from 1895 that sent shock waves through the scientific community looks like most modern day 2D medical X-ray images. Though it is not the newest technology, X-ray absorption...
09:08
Combined SPECT and CT Imaging to Visualize Cardiac Functionality
0 Views •
2023
Source: Alycia G. Berman, James A. Schaber, and Craig J. Goergen, Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana Here we will demonstrate the fundamentals of single-photon emission computed tomography/computed tomography (SPECT/CT) imaging using mice. The technique involves injecting a radionuclide into a mouse, imaging the animal after it is distributed throughout the body, and then reconstructing the produced images to create a volumetric dataset. This can...
01:21
Focused Ion Beam Scanning Electron Microscopy for 3D Reconstruction of Synaptically Linked Neurons
0 Views •
2025
Take a fixed section of mouse cortical brain tissue exhibiting neuronal axons and dendrites. The dendrites possess protrusions, known as dendritic spines, which form synapses with axons.Incubate the tissue with osmium-ferrocyanide, which binds to lipids, followed by another osmium application, which enhances structural contrast for imaging.Stain with a heavy metal compound that binds to macromolecules and enhances contrast.Dehydrate using increasing alcohol concentrations for resin...
FAQs
Reconstruction algorithms combine detector measurements collected from multiple viewing angles to estimate the X-ray attenuation associated with each voxel. The resulting voxel distribution forms the basis of cross-sectional anatomy, allowing differences within bones, organs, vessels, tumors, and other structures to be represented for biological analysis rather than remaining only as separate projection measurements.
Filtered back projection and iterative methods are two reconstruction approaches that convert projection data into an estimated attenuation map. Both support formation of cross-sectional images, but they represent alternative computational strategies for processing the same type of measurements. Comparing these approaches is relevant when image quality, noise reduction, and dose efficiency influence biological interpretation.
Noise reduction can make anatomical patterns easier to evaluate, while dose efficiency supports image acquisition with attention to X-ray exposure. Together, these improvements are important when researchers need quantitative measurements or repeated observations. They can strengthen the usefulness of reconstructed images for clinical assessment, biological research, and longitudinal studies that follow anatomical changes over time.
The workflow begins with detectors recording how tissues attenuate X-rays from multiple angles. Reconstruction software then processes those projection measurements to estimate attenuation values throughout the sampled volume, organizing the estimates into voxels and cross-sectional images. Subsequent biological analysis can examine anatomical structures or changes represented in the reconstructed data.
Researchers can apply reconstructed CT images when they need to examine internal anatomy without relying only on visible or surface features. Supported uses include studying bones, organs, blood vessels, tumors, and other anatomical changes. The approach is especially relevant to research designs that compare anatomy quantitatively or monitor changes across longitudinal observations.
The images provide a spatial distribution of estimated X-ray attenuation values across voxels, which makes internal anatomical structures available for study. This information can support analysis of normal or altered bones, organs, blood vessels, tumors, and related anatomical changes. Its value lies in connecting computational image formation with measurable biological structure and change.