eScience Institute Faculty Research
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Item type: Item , MRI2MRI weights for transformations between T1-weighted and T2-weighted MRI images(2019-09-06) Xiao, Sa; Lee, Aaron; Rokem, ArielDifferent brain MRI contrasts represent different tissue properties and are sensitive to different artifacts. The relationship between different contrasts is therefore complex and nonlinear. We developed a deep convolutional network that learns the mapping between different MRI contrasts. Using a publicly available dataset, we demonstrate that this algorithm accurately transforms between T1- and T2-weighted images, proton density images, time-of-flight angiograms, and diffusion MRI images. We demonstrate that these transformed images can be used to improve spatial registration between MR images of different contrasts.Item type: Item , Data for evaluation of fast kurtosis imaging, b-value optimization and exploration of diffusion MRI contrast(2017-04-17) Hansen, Brian; Jespersen, Sune NørhøjData was acquired in one normal volunteer using a Siemens Trio 3 T equipped with a 32 channel head coil and a double spin echo DW EPI sequence. Motion of the subject's head during acquisition was avoided by padding inside the coil. DWI data was recorded at b=0 ms μm−2, and along 33 directions at b-values from 0.2–3 ms μm−2 in steps of 0.2 ms μm−2. The encoding scheme was constructed as a combination of a 24 point spherical design and the nine directions identified for rapid kurtosis estimation in ref. 22. CSF suppression (inversion recovery) was employed. Imaging parameters were TR=7200 ms, TE=116 ms, TI=2100 ms, 19 consecutive slices were acquired at isotropic resolution of 2.5 mm, matrix size 96×96, phase encoding direction A.-P. SNR~39 at b=0 evaluated using the mean signal across all tissue types. Data were converted from the original dicom files using dcm2niix. Anatomical data is also provided. This data consists of a 1 mm isotropic T1 weighted 3D MPRAGE acquired in the sagittal orientation, matrix size 256 × 256 × 176. Scan parameters were: TE=3.7 ms, TR=2430 ms, Inversion time (TI)=960 ms, Flip angle=9°, 2 averages.Item type: Item , Dipy Data: NTU Taiwan DSI(2017-03-31) Rokem, ArielAdvanced Biomedical MRI Lab at National Taiwan University Hospital (termed the NTU Lab in the following agreements) hereby grants a license to use images and data that appears on this webpage solely for non-commercial educational and research purposes, subject to the following restrictions: (1) You must at all times acknowledge and attribute ownership of the distributed images and data to the NTU Lab in any documentation, advertising materials, and other materials related to this distribution. (2) Redistribution and use of the image are permitted provided that this paragraph are duplicated in all such forms. As the images and data is experimental in nature and is being provided solely to facilitate medical, academic and scientific research, you agree that you will use this information, images, and data at your own risk and without recourse or liability of any kind to NTU Lab. NTUH ADVANCED BIOMEDICAL MRI LAB MAKES NO REPRESENTATIONS AND EXTENDS NO WARRANTIES OF ANY KIND, EITHER EXPRESSED OR IMPLIED WITH RESPECT TO THE INFORMATION, IMAGES AND DATA, AND THERE ARE NO EXPRESS OR IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Use of the information, images or data for any commercial purposes is strictly prohibited without the express written consent of the NTU Lab.Item type: Item , Dipy data: datasets_multi-site_all_companies(2017-04-12) Rokem, ArielThis data is used by the Dipy software library (http://dipy.org). This data-set contains b=0 data from multiple vendors and multiple field strengthsItem type: Item , Dipy data: viz icons(2017-04-12) Rokem, ArielThis data is used by the Dipy software library (http://dipy.org)Item type: Item , Dipy data: exp_bundles_and_maps(2017-04-12) Rokem, ArielThis data is used by the Dipy software library (http://dipy.org)Item type: Item , Dipy data: syn_test(2017-04-12) Rokem, ArielThis data is used by the Dipy software library (http://dipy.org) This data-set contains a b=0 image and T1-weighted image, that are used to test the SyN algorithmItem type: Item , Dipy Data: sherbrooke_3shell(2017-04-12) Rokem, ArielData to be used as part of the Dipy software (http://dipy.org) This data-set contains HARDI data acquired with 193 different gradientsItem type: Item , Dipy Data: Sherbrooke 3-shell(2017-03-31) Rokem, ArielA 3shell HARDI dataset with 192 gradient directionItem type: Item , Dipy Data: ISBI 2013(2017-03-31) Rokem, ArielThis is a data-set to be used together with Dipy (http://dipy.org)Item type: Item , Templates for Automated Fiber Quantification of human corpus callosum from Diffusion MRI data(2016-01-27)These templates are used to segment human white matter into the major tracks, as described in Yeatman et al. 2012 (Yeatman JD, Dougherty RF, Myall NJ, Wandell BA, Feldman HM (2012) Tract Profiles of White Matter Properties: Automating Fiber-Tract Quantification. PLoS ONE 7(11): e49790. doi:10.1371/journal.pone.0049790). Briefly, The regions of interest (ROIs) in these templates are defined in locations that isolate the central portion of the track where the fibers are coherently bundled together and before they begin diverging towards cortex. Each waypoint ROI was drawn on a group-average DTI data set in MNI space based on the anatomical prescriptions defined in Wakana et al (Wakana S, Caprihan A, Panzenboeck MM, Fallon JH, Perry M, et al. (2007) Reproducibility of quantitative tractography methods applied to cerebral white matter. Neuroimage 36: 630–644. doi: 10.1016/j.neuroimage.2007.02.049).Item type: Item , ICBM 2009a Nonlinear Asymmetric MNI brain template(McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University., 2015-07-15) Louis, CollinsCopyright (C) 1993–2004 Louis Collins, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University. Permission to use, copy, modify, and distribute this software and its documentation for any purpose and without fee is hereby granted, provided that the above copyright notice appear in all copies. The authors and McGill University make no representations about the suitability of this software for any purpose. It is provided “as is” without express or implied warranty. The authors are not responsible for any data loss, equipment damage, property loss, or injury to subjects or patients resulting from the use or misuse of this software package.Item type: Item , Diffusion MRI measured at multiple b-values(2015-07-13) Romain, ValabregueDiffusion MRI at multiple b-values (200, 400, 1000, 2000, 3000) was collected on a 3T Siemens Prisma MRI instrument in a single healthy individual.