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OpenNeuro dataset - The Impact and Reliability of Tissue Segmentation on In Vivo Magnetic Resonance Spectroscopy Metabolite Quantification
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# The Impact and Reliability of Tissue Segmentation on In Vivo Magnetic Resonance Spectroscopy Metabolite Quantification Contact: [mam4041@med.cornell.edu](mailto:mam4041@med.cornell.edu) ## Overview These data were collected as part of a study to assess the test-retest reliability of multi-metabolite edited MRS editing schemes and the [sLASER](https://doi.org/10.1002/mrm.21302) localization approach. The resulting dataset was also used to evaluate the impact of anatomical segmentation on estimated metabolite concentrations. Data types included are defaced *T*<sub>1</sub>-weighted 3D structural MRI images and sLASER data. ## Methods ### Subjects Sixteen healthy adults (10 females, 6 males, mean age = 38.4 years). ### MR protocol MR data were acquired using a 3T GE Discovery MR750 MRI scanner using a <sup>1</sup>H 32-channel RF phased-array head coil for receive and a body coil for transmit. #### MRI *T*<sub>1</sub>-weighted FSPGR BRAVO structural MRI acquisition parameters: - Voxel resolution = 0.9 × 0.9 × 1.5 mm<sup>3</sup> - TE/TR/TI (ms) = 5.2/12.2/725 - Flip angle = 7° - Slices = 124 - FOV = 256 × 256 mm<sup>2</sup> - Matrix size = 256 × 256 - Parallel acquisition technique: GRAPPA - Parallel acquisition factor: 2 #### MRS General MRS acquisition parameters: - Volume of interest = medial parietal lobe - Voxel resolution = 30 × 30 × 30 mm<sup>3</sup> - Spectral width = 5000 Hz - Number of points = 4096 ##### sLASER - TE/TR = 35/2000 ms - Number of transients = 64
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OpenNeuro dataset - The Impact and Reliability of Tissue Segmentation on In Vivo Magnetic Resonance Spectroscopy Metabolite Quantification
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