Published on 10 October 2024 |

Version 2.0.0

Respiratory-triggered MRCP acquisition at 3T using a T2-weighted TSE (3D SPACE) sequence for Deep Learning-based reconstruction of MRCP

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Kim, Jinho;Nickel, Dominik;Knoll, Florian

Description

DescriptionThis dataset is the sample data for MRCP_DLRecon (GitHub). Place this dataset in the "Sample_data/" directory along with the "dataset.csv" file. DataThe provided 3D MRCP data were acquired at 3T (Skyra, Siemens Healthineers AG, Erlangen) using the 3D-SPACE (3D T2w TSE) sequence for a single healthy volunteer. We provide two 2x  and one 6x 3D MRCP data to ensure various training and testing scenarios. Each data in the HDF5 format contains the following structures:Datasetsgrappa: target data (y * x * slice)kdata_raw: Raw k-space data (x2 or x6) (nCoil * PE * RO * slice)kdata_fs: Fully-sampled k-space data from kdata_raw using GRAPPA (nCoil ×× PE ×× RO ×× Slice)sm_espirit: ESPIRiT-based sensitivity maps (nCoil * y * x * slice)CitationPlease cite the following paper if this dataset is helpful for your research :)Kim, J., Nickel, M. and Knoll, F. (2025), Deep Learning-Based Accelerated MR Cholangiopancreatography Without Fully-Sampled Data. NMR in Biomedicine, 38: e70002. https://doi.org/10.1002/nbm.70002

Citations (0)

Mentions (0)

Metrics

Dataset Index

1.7

FAIR Score

69%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Zenodo

Assigned Domain

Subfield

Artificial Intelligence

Field

Computer Science

Domain

Physical Sciences

Confidence Score

44%

Source

Scholar Data Model

Normalization Factors

FT

13.46

CTw

1.00

MTw

1.00