Search results
Results from the WOW.Com Content Network
(a) CT scan of the head. (b) MRI machine. (c) PET scans produce images of active blood flow and physiological activity in the targeted organ or organs. (d) Ultrasound technology to monitor pregnancy. Medical imaging is a range of imaging techniques and technologies that enables clinicians to visualize the internal structures of the human body.
Examples include registration of brain CT/MRI images or whole body PET/CT images for tumor localization, registration of contrast-enhanced CT images against non-contrast-enhanced CT images [15] for segmentation of specific parts of the anatomy, and registration of ultrasound and CT images for prostate localization in radiotherapy.
The Brain Imaging Data Structure (BIDS) is a standard for organizing, annotating, and describing data collected during neuroimaging experiments. It is based on a formalized file and directory structure and metadata files (based on JSON and TSV ) with controlled vocabulary . [ 1 ]
Amira (ah-MEER-ah) is a software platform for visualization, processing, and analysis of 3D and 4D data. It is being actively developed by Thermo Fisher Scientific in collaboration with the Zuse Institute Berlin (ZIB), and commercially distributed by Thermo Fisher Scientific — together with its sister software Avizo.
The Neuroimaging Informatics Technology Initiative (NIfTI) is an open file format [1] commonly used to store brain imaging data obtained using Magnetic Resonance Imaging methods. References [ edit ]
A particularly notable subset of MRI is magnetic resonance angiography, which is a group of techniques used to image arteries and veins. MRI's imaging utility is further expanded upon by diffusion MRI and functional MRI, which can be used to capture neuronal tracts and blood flow respectively.
Radiomics can also be used to identify challenging physiological events such as brain activity, which is usually studied with imaging techniques such as functional MRI "fMRI". FMRI raw images can undergo radiomic analysis to generate imaging features that can be later correlated with meaningful brain activity. [50]
An image segmentation neural network can process small areas of an image to extract simple features such as edges. [81] Another neural network, or any decision-making mechanism, can then combine these features to label the areas of an image accordingly. A type of network designed this way is the Kohonen map.