开发和验证用于海马子场自动细分的质量控制程序
Kelsey L Canada1, Samaah Saifullah1, Jennie C Gardner2,3
1Institute of Gerontology, Wayne State University, Detroit, Michigan, USA.
Hippocampus
|May 29, 2023
概括
质量控制对于自动脑MRI细分至关重要. 这项研究引入了一种可靠,高效的程序,用于验证海马体自动子场细分,确保精确的神经成像研究.
科学领域:
- 神经成像是一种神经成像.
- 医学图像分析 医学图像分析
- 计算神经科学是一种神经科学.
背景情况:
- 在体内磁共振成像 (MRI) 中的自动细分提供了效率和可重现性.
- 然而,自动细分方法的准确性需要严格的验证,因为它们可能始终错误.
- 目前神经成像研究中的质量控制 (QC) 实践对于应用研究来说是不够的.
研究的目的:
- 为了呈现一个详细的,验证的质量控制 (QC) 和自动海马子场细分的校正程序.
- 建立一种可靠的方法,以确保自动神经成像测量的有效性.
- 为研究中实施和测试质量控制程序提供一个框架.
主要方法:
- 开发一种两步质量控制程序,用于识别细分错误.
- 创建一个错误分类和一个错误严重性评级尺度,用于系统评估.
- 在具有不同成像参数的独立数据集上的QC程序的交叉验证,并由独立评级人员进行.
主要成果:
- 质量控制程序在错误识别和手动纠正方面表现出高之间的可靠性.
- 手动校正在体积测量中带来了最大3%的误差差.
- 对错误频率的分析显示,不同数据集和评分器之间没有系统偏差的证据.
结论:
- 提出的质量控制程序是高效的,可靠的,并优先考虑自动地图的测量有效性.
- 这种方法提高了神经成像研究中自动细分的可靠性.
- 为更广泛的采用提供了实施和假设测试策略的建议.
相关概念视频
01:05Quality Control
Quality control is one of the three cyclical quality assurance activities that help keep a system under statistical control. Typical quality control activities include creating quality control charts, conducting proficiency testing, and documenting and archiving results.
Quality control helps track data, visualize trends, and identify variations, making it easier to detect deviations that may affect the accuracy of an analysis. One way to do this is by generating a quality control chart, which...
Quality control helps track data, visualize trends, and identify variations, making it easier to detect deviations that may affect the accuracy of an analysis. One way to do this is by generating a quality control chart, which...
01:19Quality Assurance
Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...
01:15Data Validation
Method validation is a crucial process in analytical chemistry designed to confirm that a given method consistently produces reliable and high-quality results. This process is essential when a method is applied to different sample matrices or when procedural modifications are made, ensuring that the results meet acceptable standards across various applications.
Key parameters for method validation include:
Key parameters for method validation include: