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CONN includes a user-friendly GUI to manage all aspects of functional connectivity analyses, [1] including preprocessing of functional and anatomical volumes, [2] elimination of subject-movement and physiological noise, [3] outlier scrubbing, [4] estimation of multiple connectivity and network measures, and population-level hypothesis testing.
COSMOS assumes a model-free susceptibility distribution and keeps full fidelity to the measured data. This method has been validated extensively in in vitro, ex vivo and phantom experiments. Quantitative susceptibility maps obtained from in vivo human brain imaging also showed high degree of agreement with previous knowledge about brain anatomy ...
MONAI provides a robust suite of libraries, tools, and Software Development Kits (SDKs) that encompass the entire process of building medical imaging applications. It offers a comprehensive range of resources to support every stage of developing Artificial intelligence (AI) solutions in the field of medical imaging, from initial annotation (MONAI Label), [2] through models development and ...
57,541 copies of the FreeSurfer software package have been registered for use as of April 2022 [5] and it is a core tool in the processing pipelines of the Human Connectome Project, [6] the UK Biobank, [7] the Adolescent Brain Cognitive Development Study, [8] and the Alzheimer's Disease Neuroimaging Initiative.
The FMRIB Software Library, abbreviated FSL, is a software library containing image analysis and statistical tools for functional, structural and diffusion MRI brain imaging data. FSL is available as both precompiled binaries and source code for Apple and PC computers. It is freely available for non-commercial use.
Susceptibility weighted imaging (SWI), originally called BOLD venographic imaging, is an MRI sequence that is exquisitely sensitive to venous blood, hemorrhage and iron storage. SWI uses a fully flow compensated, long echo, gradient recalled echo (GRE) pulse sequence to acquire images.
Harmonic phase (HARP) algorithm [1] is a medical image analysis technique capable of extracting and processing motion information from tagged magnetic resonance image (MRI) sequences. It was initially developed by N. F. Osman and J. L. Prince at the Image Analysis and Communications Laboratory at Johns Hopkins University. The method uses ...
Analysis of Functional NeuroImages (AFNI) is an open-source environment for processing and displaying functional MRI data—a technique for mapping human brain activity. AFNI is an agglomeration of programs that can be used interactively or flexibly assembled for batch processing using shell script .
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