分割
人工智能
计算机科学
全自动
神经影像学
模式识别(心理学)
图像分割
计算机视觉
神经科学
心理学
机械工程
工程类
作者
Mohammad Ali,Jee Su Suh,Milita Ramonas,Stefanie Hassel,Stephen R. Arnott,Stephen C. Strother,Luciano Minuzzi,Roberto B. Sassi,Raymond W. Lam,Roumen Milev,Daniel J. Müller,Valerie H. Taylor,Sidney H. Kennedy,Benício N. Frey
出处
期刊:MethodsX
[Elsevier BV]
日期:2022-01-01
卷期号:9: 101864-101864
被引量:1
标识
DOI:10.1016/j.mex.2022.101864
摘要
The hypothalamus is a small grey matter structure which plays a crucial role in many physiological functions. Some studies have found an association between hypothalamic volume and psychopathology, which stresses the need for a standardized method to maximize segmentation accuracy. Here, we provide a detailed step-by-step method outlining the procedures to manually segment the hypothalamus using anatomical T1w images from 3T scanners, which many neuroimaging studies collect as a standard anatomical reference image. We compared volumes generated by manual segmentation and those generated by an automatic algorithm, observing a significant difference between automatically and manually segmented hypothalamus volumes on both sides (left: U = 222842, p-value < 2.2e-16; right: U = 218520, p- value < 2.2e-16).•Significant difference exists between existing automatic segmentation methods and the manual segmentation procedure.•We discuss potential drift effects, segmentation quality issues, and suggestions on how to mitigate them.•We demonstrate that the present manual segmentation procedure using standard T1-weighted MRI may be significantly more accurate than automatic segmentation outputs.
科研通智能强力驱动
Strongly Powered by AbleSci AI