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Magnetic Resonance Imaging

ISSN: 0730-725X

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Datasets associated with articles published in Magnetic Resonance Imaging

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1970
2024
1970 2024
9 results
  • Data for: Test-retest reliability and reproducibility of long-label pseudo-continuous arterial spin labeling
    test-retest CBF
    • Dataset
  • Data for: Compressed MRI reconstruction exploiting a rotation-invariant total variation discretization
    This MATLAB package will reproduce the results of the proposed method in "Compressed MRI reconstruction exploiting a rotation-invariant total variation discretization".
    • Dataset
  • Data for: Compressed MRI reconstruction exploiting a rotation-invariant total variation discretization
    This MATLAB package will reproduce the results of the proposed method in the paper "Compressed MRI reconstruction exploiting a rotation-invariant total variation discretization".
    • Dataset
  • Data for: Compressed MRI reconstruction exploiting a rotation-invariant total variation discretization
    This MATLAB package will reproduce the results of the proposed method in the paper "Compressed MRI reconstruction exploiting a rotation-invariant total variation discretization".
    • Dataset
  • Data for: Group Delay Method for MRI Aortic Pulse Wave Velocity Measurements in Clinical Protocols with Low Temporal Resolution: Validation in a Heterogeneous Cohort
    Data for manuscript "Group Delay Method for MRI Aortic Pulse Wave Velocity Measurements in Clinical Protocols with Low Temporal Resolution: Validation in a Heterogeneous Cohort".
    • Dataset
  • Data for: Fully Automated and Comprehensive Left-Ventricular Contractility Analysis in Long-term Survivors of Breast Cancer Patients after Chemotherapy
    Example full dataset of DENSE MRI data
    • Dataset
  • Data for: Motion-Compensated Reconstruction of Magnetic Resonance Images from Undersampled Data
    These data files contain the multi-channel MRI k-space information to reconstruct the images for the paper "Motion-Compensated Reconstruction of Magnetic Resonance Images from Undersampled Data" submitted to Magnetic Resonance Imaging by Daniel Weller, Luonan Wang, John Mugler, and Craig Meyer. Each zip file contains a MATLAB workspace file (.mat) and a readme.txt file explaining the contents of that workspace file.
    • Dataset
  • jostenson/MRI_Ostenson_MRF_MFI: Replication code for: Multi-frequency interpolation in spiral magnetic resonance fingerprinting for correction of off-resonance blurring
    In the MRI method of magnetic resonance fingerprinting (MRF) pulse sequences often employ spiral trajectories for data readout. Spiral k-space acquisitions are vulnerable to blurring in the spatial domain in the presence of static field off-resonance. The code here applies a blurring correction algorithm for use in spiral MRF. The supplied data with the executed code demonstrate the correction's effectiveness in phantom and in vivo experiments. Results show that image quality of T1 and T2 parametric maps is improved by application of this correction. This MRF correction has negligible effect on the concordance correlation coefficient and improves coefficient of variation in regions of off-resonance relative to uncorrected measurements.
    • Software/Code
  • Data From QIN PROSTATE
    This collection contains multiparametric MRI images collected for the purposes of detection and/or staging of prostate cancer. The MRI parameters include T1- and T2-weighted sequences as well as Diffusion Weighted and Dynamic Contrast-Enhanced MRI. The images were obtained using endorectal and phased array surface coils at 3.0T (GE Signa HDx 15.0) The value of this collection is to provide clinical image data for the development and evaluation of quantitative methods for prostate cancer characterization using multiparametric MRI. Data was provided by Brigham and Women's Hospital, PI Dr. Fiona Fennessy. MR imaging exam was performed on a GE Signa HDx 3.0 T magnet (GE Healthcare, Waukesha, WI) using a combination of 8-channel abdominal array and endorectal coil (Medrad, Pittsburgh, PA). The MR sequences included T1- and T2-weighted imaging, diffusion weighted (DW) imaging, and DCE MRI. T1-weighted imaging was performed with a spoiled gradient recalled echo (SPGR) sequence with TR/TE/α = 385 ms/6.2 ms/65° over a (16 cm)2 field of view (FOV). T2-weighted imaging was performed with a FRFSE (Fast Recovery Fast Spin Echo) sequence with TR/TE = 3500/102 ms, FOV = (16 cm)2. A DW echo planar imaging sequence with trace diffusion sensitization and b-values of 0 and 500 s/mm2, and TR/TE = 2500/65 ms provided data for an Apparent Diffusion Coefficient (ADC) map. Finally, DCE MRI utilized a 3D SPGR sequence with TR/TE/α = 3.6 ms/1.3 ms/15°, FOV = (26 cm)2, with full gland coverage and reconstructed image voxel size of 1×1×6 mm (interpolated to 256×256 matrix). DCE MRI frames were acquired at approximately 5 s intervals (the number of frames varied between 12 and 16 slices resulting in the time resolution between 4.4 and 5.3 seconds) to achieve a clinically appropriate compromise between spatial and temporal resolutions. Gadopentetate dimeglumine (Magnevist, Berlex Laboratories, Wayne, New Jersey) was injected intravenously using a syringe pump (0.15 mmol/kg) at the rate of 3 ml/s followed by 20 ml saline flush at the same rate. The protocol included ~ 5 baseline scans prior to contrast injection for estimation of baseline tissue properties.
    • Dataset