共 1 条
Towards Optimising MRI Characterisation of Tissue (TOMCAT) Dataset including all Longitudinal Automatic Segmentation of Hippocampal Subfields (LASHiS) data
被引:3
|作者:
Shaw, Thomas B.
[1
]
York, Ashley
[2
]
Barth, Markus
[1
,3
,4
]
Bollmann, Steffen
[1
,4
]
机构:
[1] Univ Queensland, Ctr Adv Imaging, Brisbane, Qld, Australia
[2] Univ Queensland, Sch Psychol, Brisbane, Qld, Australia
[3] Univ Queensland, Sch Informat Technol & Elect Engn, Brisbane, Qld, Australia
[4] Univ Queensland, ARC Training Ctr Innovat Biomed Imaging Technol, Brisbane, Qld, Australia
来源:
基金:
澳大利亚研究理事会;
澳大利亚国家健康与医学研究理事会;
关键词:
Hippocampus;
Longitudinal studies;
Segmentation;
Magnetic resonance imaging;
Image processing;
Computer-assisted;
D O I:
10.1016/j.dib.2020.106043
中图分类号:
O [数理科学和化学];
P [天文学、地球科学];
Q [生物科学];
N [自然科学总论];
学科分类号:
07 ;
0710 ;
09 ;
摘要:
Seven healthy participants were scanned using a Siemens Magnetom 7 Tesla (T) whole-body research MRI scanner (Siemens Healthcare, Erlangen, Germany). The first scan session was acquired in 2016 (time point one), the second and third session in 2019 (time point two and three, respectively) with the third session acquired 45 min following the second as a scan-rescan condition. The following scans were acquired for all time points: structural T1 weighted (T1w) MP2RAGE, high in-plane resolution Turbo-Spin Echo (TSE) dedicated for hippocampus subfield segmentation. The data were used in three projects to date, for more insight see: 1) Non-linear realignment for Turbo-Spin Echo retrospective motion correction and hippocampus segmentation improvement [1] 2) Longitudinal Automatic Segmentation of Hippocampal Subfields (LASHiS) using multi-contrast MRI [2]. 3) The challenge of bias-free coil combination for quantitative susceptibility mapping at ultra-high field [3]. Data were converted from DICOM to nifti format following the Brain Imaging Data Structure (BIDS) [4]. Data were analysed for the accompanying manuscript "Longitudinal Automatic Segmentation of Hippocampal Subfields (LASHiS) using multi-contrast MRI" including test-retest reliability and longitudinal Bayesian Linear Mixed Effects (LME) modelling. (C) 2020 The Author(s). Published by Elsevier Inc.
引用
收藏
页数:7
相关论文