Curator Dashboard

About 1.2GB of anonymized imaging data of many different file formats used by the BRAINS suite of tools (BRAINSFit, GTRACT, BRAINS, BRAINSTracer... and others) as a common set of anonymized data for nightly regression testing.

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• SciCrunch
• 13 years ago - by Anonymous

Human DTI brain atlases have been generated at UNC-Chapel Hill for several age groups, by iterative joint deformable registration of training datasets into a single unbiased DTI average image. Atlases packages include an atlas DTI tensor image, atlas DTI property images (FA, MD, AD, RD), and single tensor tractography based fiber tracts of major tracts with related 3D planes for fiber profile information: genu, splenium, anterior and posterior limb of internal capsule, uncinate fasciculus.

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• SciCrunch
• 13 years ago - by Anonymous

The methodology and applications of task independent fluctuation measures including: connectivity maps of fMRI resting state scans, research using EEG/MEG/PET etc, methods to remove non-neural fluctuations, and applications to clinical populations.

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• SciCrunch
• 13 years ago - by Anonymous

While the traditional temporally concatenated Group ICA (TC-GICA) adopting three steps of PCA reduction, it could result in inconsistent and variable components when different subject orders were used, both for the group- and individual-level results. Such instability can further cause instable and thus unreliable statistical results. Subject Order-Independent Group ICA (SOI-GICA) aims to fix this problem by producing stable and reliable GICA results. For details please see the paper Subject Order-Independent Group ICA (SOI-GICA) for Functional MRI Data Analysis (Zhang et al., 2010, NeuroImage)(http://dx.doi.org/10.1016/j.neuroimage.2010.03.039). MICA is the toolbox inplemented SOI-GICA for convenience of usage.

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• SciCrunch
• 13 years ago - by Anonymous

Script which points browser to Nathan Kline Institute (NKI) Rockland Sample.

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• SciCrunch
• 13 years ago - by Anonymous

An open source implementation of a non-rigid groupwise registration method. This project is implemented by Serdar K Balci (serdar at csail.mit.edu) and supervised by Polina Golland and William M. Wells All metrics are implementing in a multi-threaded fashion. The algorithm will run faster on computers with multiple CPU''s.

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• SciCrunch
• 13 years ago - by Anonymous

Tool that associates localized white matter (WM) lesions with disruptions in gray matter connectivity as a step toward understanding the lesions? functional implications. A Tractogram Reference Set (TRS), i.e. collections of white matter fibers, is constructed from 73 normal healthy individuals and coregistered to a common space (MNI). The NeMo Tool uses the TRS to assess structural network disruption due to a particular WM lesion mask on a region and network-wise level. This tool is an easy way for researchers and clinicians to investigate changes in the structural brain network without having to perform tractography on their own normal data or on diseased/injured brains where the results may not represent the underlying physiology.

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• SciCrunch
• 13 years ago - by Anonymous

Bibliography of books related to neuroscience addressing the topic of functional and structural neuroimaging.

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• SciCrunch
• 13 years ago - by Anonymous

This program contains Python modules for modeling and reconstruction of diffusion weighted MRI data. It is a subset of the code internally used in the CVGMI lab at the University of Florida. Three different reconstruction methods are currently included in this program, namely, Mixture of Wisharts (MOW), Diffusion Orientation Transform (DOT) and Q-ball Imaging (QBI). This program is mainly developed and maintained by Bing Jian, as part of his Ph.D. research, supervised by Prof. Baba Vemuri. Please note that the source code of this program is hosted at Google Code, see the Source Code link on the left.

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• SciCrunch
• 13 years ago - by Anonymous

Data set of an AFNI GroupInCorr session for multi-echo independent component regression (ME-ICR) for a cohort of 52 subjects. This dataset provides a high-quality atlas of seed-based functional connectivity with strong statistical conditioning.

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• SciCrunch
• 13 years ago - by Anonymous

An on-line tutorial on how to use MATLAB for Diffusion-Weighted MRI processing. The following subjects are covered in this tutorial: Generation of Synthetic Diffusion-Weighted MRI datasets, Diffusion Tensor (DTI) Estimation from DW-MRI, DTI Visualization as a field of ellipsoids, Higher-order Diffusion Tensor Estimation from DW-MRI, Computing of Tensor Orientation Distribution Functions (Tensor ODF), Computing of Fiber Orientations, Higher-order Diffusion Tensor Image Visualization as fields of spherical functions, Multi-fiber reconstruction etc. The tutorial contains numerous illustrations, figures and Matlab scripts embedded in the text. The reader/user can automatically generate Matlab script for a self-designed DW-MRI experiment by selecting which steps needs to be followed. The code that corresponds to the selected steps is then appropriately merged in the Matlab Script Generator, and the user can easily copy and paste the produced code directly to the Matlab command prompt.

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• SciCrunch
• 13 years ago - by Anonymous

This repository stores and provides opportunities for collaboration through Matlab code, libraries, and configuration information for projects in early stage development. The MASI research laboratory concentrates on analyzing large-scale cross-sectional and longitudinal neuroimaging data. Specifically, they are interested in population characterization with magnetic resonance imaging (MRI), multi-parametric studies (DTI, sMRI, qMRI), and shape modeling.

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• SciCrunch
• 13 years ago - by Anonymous

Tool that provides a unified framework for testing and applying statistical and voting label fusion techniques. The project will include implementations of several different voting techniques including majority vote, weighted voting, and regionally weighted voting. Additionally, multiple statistical fusion methods will be included, notably, STAPLE, Spatial STAPLE, STAPLER and COLLATE. In addition to the fusion algorithms, code for running specialized simulations and various tools and utilities to test the efficacy of the algorithms will be provided.

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• SciCrunch
• 13 years ago - by Anonymous

Software using a novel local label learning strategy to estimate the target image?s segmentation label using statistical machine learning techniques. They used a support vector machine (SVM) with a K nearest neighbor (KNN) based training sample selection strategy to learn a classifier for each of the target image voxel based on a training dataset consisting of its neighboring voxels in the atlases. Validation experiments on hippocampus segmentation of 117 MR images demonstrated that the method can produce segmentation results consistently better than state-of-the-art label fusion methods.

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• SciCrunch
• 13 years ago - by Anonymous

Project to provide long-term hosting and release for small tools related to medical image analysis. Source repository contains highly experimental code intended for collaborative development. However, any interested parties are welcome to browse/reuse code. Stable/evolved projects will be moved to independent projects.

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• SciCrunch
• 13 years ago - by Anonymous

This module reduces Rician noise on nhdr/nrrd DWIs. Filters image in mean squared error sense using Rician noise model. All estimations are performed as sample estimates in a "shaped neighborhood" defined by the weights extracted from structural similarity of voxels following same idea as in Non-Local Means filter.

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• SciCrunch
• 13 years ago - by Anonymous

Automatically creates a mask based on the "foreground" of an anatomical scan volume.

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• SciCrunch
• 13 years ago - by Anonymous

This repository stores plugins, tutorial code, and examples demonstrating MRI manipulation within the MIPAV plugin environment. This project is separate from JIST so that we can provide WRITE access to any interested party without overly exposing the infrastructure to unplanned modification. Please contact the administrators if you would like to join this project - open use is encouraged.

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• SciCrunch
• 13 years ago - by Anonymous

This project is used for students enrolled in courses using the JIST framework. Content in this CVS is freely available, but it is not intended for any specific purpose.

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• SciCrunch
• 13 years ago - by Anonymous

Primate brain atlas created from over 100 structural MR scans of 19 rhesus macaque animals. The atlas currently comprises high-resolution T1-weighted average MR images with and without skull stripping, tissue probability maps, and a detailed parcellation map based on the NeuroMaps atlas.

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• SciCrunch
• 13 years ago - by Anonymous