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Caret Van Essen Lab, Washington University in St. Louis; CONN (functional connectivity toolbox) Diffusion Imaging in Python (DIPY) [1] DL+DiReCT [2] EEGLAB; FMRIB Software Library (FSL) FreeSurfer; Computational anatomy toolbox; Imaris Imaris for Neuroscientists; ISAS (Ictal-Interictal SPECT Analysis by SPM) LONI Pipeline, Laboratory of Neuro ...
A number of online neuroscience databases are available which provide information regarding gene expression, neurons, macroscopic brain structure, and neurological or psychiatric disorders. Some databases contain descriptive and numerical data, some to brain function, others offer access to 'raw' imaging data, such as postmortem brain sections ...
Medical image segmentation is made difficult by low contrast, noise, and other imaging ambiguities. Although there are many computer vision techniques for image segmentation, some have been adapted specifically for medical image computing. Below is a sampling of techniques within this field; the implementation relies on the expertise that ...
In the following, the image is segmented into non-brain and brain tissue, with the latter usually being sub-segmented into at least gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF). Since image voxels near the class boundaries do not generally contain just one kind of tissue, partial volume effects ensue that can be corrected for.
The first MR images of a human brain were obtained in 1978 by two groups of researchers at EMI Laboratories led by Ian Robert Young and Hugh Clow. [1] In 1986, Charles L. Dumoulin and Howard R. Hart at General Electric developed MR angiography, [2] and Denis Le Bihan obtained the first images and later patented diffusion MRI. [3]
Computer-aided detection (CADe), also called computer-aided diagnosis (CADx), are systems that assist doctors in the interpretation of medical images.Imaging techniques in X-ray, MRI, endoscopy, and ultrasound diagnostics yield a great deal of information that the radiologist or other medical professional has to analyze and evaluate comprehensively in a short time.
Image registration or image alignment algorithms can be classified into intensity-based and feature-based. [3] One of the images is referred to as the moving or source and the others are referred to as the target, fixed or sensed images. Image registration involves spatially transforming the source/moving image(s) to align with the target image.
In the early 2000s, the field of neuroimaging reached the stage where limited practical applications of functional brain imaging have become feasible. The main application area is crude forms of brain–computer interface. The world record for the spatial resolution of a whole-brain MRI image was a 100-micrometer volume (image) achieved in 2019.