Database of human brain images derived from a realistic phantom and generated using a sophisticated MRI simulator. Custom simulations may be generated to match a user's selected parameters. The goal is to aid validation of computer-aided quantitative analysis of medical image data. The SBD contains a set of realistic MRI data volumes produced by an MRI simulator. These data can be used by the neuroimaging community to evaluate the performance of various image analysis methods in a setting where the truth is known. The SBD contains simulated brain MRI data based on two anatomical models: normal and multiple sclerosis (MS). For both of these, full 3-dimensional data volumes have been simulated using three sequences (T1-, T2-, and proton-density- (PD-) weighted) and a variety of slice thicknesses, noise levels, and levels of intensity non-uniformity. These data are available for viewing in three orthogonal views (transversal, sagittal, and coronal), and for downloading.

Note. SNR  =  signal-to-noise ratio; CNR  =  contrast-to-noise ratio.

This dataset contains the following:

• 2500 images generated from the BrainWeb dataset [Aubert-Broche et al, IEEE TMI 2006] using an inversion recovery signal model from MRpro.
• A set of pre-trained weights of a network to estimate spatially adaptive regularization parameter weights to be used in the total variation (TV)-minmization example in MRpro.
• A brain MR scan of a healthy volunteer obtained with an OSI2 ONE ultra-low field scanner (https://www.opensourceimaging.org/project/osii-one)

For further details, please have a look at the examples of MRpro (https://github.com/PTB-MR/mrpro).

Classification results on Brainweb T1-weighted MRI data in different levels of bias field and noise (pn).

Computational complexity, converging time, number of iterations and per iteration time (average ± standard deviation, UNIT: Second) by applying five algorithms on BrainWeb dataset.

This dataset is part of the work https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full. This is the twelfth part of 14 parts of the full dataset (12/14). It contains 3 sets of simulated T1 weighted brain volumes in 3 simulated scanning sequences of spin-echo. The parameters of simulated scanning sequences are respectively repetition time (TR) = 600ms, 700ms, 800ms, and echo time (TE) = 30ms. Under each simulated scanning sequence, there are 500 brain volumes.

The segmentation labels for each tissue are contained in the first part which you may find at https://zenodo.org/record/7294916

The simulation process of this dataset involves two processes. The first is to simulate one brain under different simulated scanning sequences. For this, we use BrainWeb https://brainweb.bic.mni.mcgill.ca/cgi/bw/submit_request. In the custom setting, we use spin-echo and apply image artifact the same as the default setting of this page. The second process is to transform each simulated brain from BrainWeb to different anatomical shapes. We use Human Connectome Project (HCP) 1200 subject data https://www.humanconnectome.org/study/hcp-young-adult and randomly select 500 brains as anatomical references.

Other details of this dataset can be found at https://www.frontiersin.org/articles/10.3389/fnimg.2022.1012639/full where the details of the data construction are discussed.

All parts of the whole dataset can be found at:

Part 1: https://zenodo.org/record/7294916

Part 2: https://zenodo.org/record/7389550

Part 3: https://zenodo.org/record/7390382

Part 4: https://zenodo.org/record/7390741

Part 5: https://zenodo.org/record/7391205

Part 6: https://zenodo.org/record/7393060

Part 7: https://zenodo.org/record/7393174

Part 8: https://zenodo.org/record/7393347

Part 9: https://zenodo.org/record/7394250

Part 10: https://zenodo.org/record/7394667

Part 11: https://zenodo.org/record/7394939

Part 12: https://zenodo.org/record/7395031

Part 13: https://zenodo.org/record/7395620

Part 14: https://zenodo.org/record/7395622

brain web 20 brain extraction

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