five

Quantitative Evaluation of apparent diffusion coefficient in a large multi-unit institution using the QIBA diffusion phantom [Data Repository]

收藏
NIAID Data Ecosystem2026-03-12 收录
下载链接:
https://figshare.com/articles/dataset/Quantitative_Evaluation_of_apparent_diffusion_coefficient_in_a_large_multi-unit_institution_using_the_QIBA_diffusion_phantom_Data_Repository_/12933938
下载链接
链接失效反馈
官方服务:
资源简介:
A sampling of 23 clinical MRI scanners was investigated in this study. DWI acquisitions with ADC reporting are performed in all of these scanners allowing for patients to be scheduled for iterative evaluation and serial imaging across different device manufacturers, models, field strengths, and acquisition parameters. In order to assess harmonization and standardization across the fleet for developing, implementing and continuously assessing a quality control program for quantitative biomarker imaging we provide an initial characterization of the variance in our institutional DWI and ADC performance across our fleet using a newly constructed jointly developed NIST/QIBA DWI phantoms (High Precision Devices Inc., Boulder, CO, USA). We also hope to utilize this information to categorize our scanners by vendor, platform, or field strength by those which are closest in terms of ADC accuracy, so that, if necessary, patients can be selectively triaged to scanners which most closely approximate the machine of their initial imaging. This initial benchmarking of the scanners using the QIBA protocol is the precursor to longitudinal assessment amongst scanners for quality assurance as well as later lending to the investigation of variance introduced by specific clinical protocols and advanced acquisition techniques (e.g., multi-shot, simultaneous multi-slice encoding, etc).
创建时间:
2020-09-09
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作