从腹部CT或MR成像中自动提取身体组成指标:范围审查
Christopher Winder1, Matthew Clark2, Russell Frood3
1UKRI CDT in AI for Medical Diagnosis and Care, University of Leeds, Woodhouse, LS2 9JT, Leeds, UK; School of Computing, University of Leeds, Woodhouse, LS2 9JT, Leeds, UK.
European journal of radiology
|October 5, 2024
概括
从腹部图像中对身体组成的自动细分是一个不断增长的研究领域. 在成像类型和队列大小中,准确性是一致的,使用体积数据可能有所改善.
科学领域:
- 医学成像分析 医学成像分析
- 身体组成评估评估
- 计算解剖学的计算解剖学
背景情况:
- 使用医学成像进行准确的身体成分分析对于了解健康和疾病至关重要.
- 自动细分方法越来越多地用于量化脂肪组织和骨肌肉.
- 对于可靠的临床翻译,需要标准化的方法.
研究的目的:
- 审查从腹部横截面成像中自动细分关键的身体组成指标的方法方法方法.
- 评估影响细分精度和临床实用性的因素.
主要方法:
- 在四个数据库中进行了系统的文献搜索,用于自动化细分研究 (2019-2023年).
- 包括的研究根据成像方式,队列大小,脊椎水平和模型维度进行了评估.
- 排除标准集中在手动方法,非腹部成像和2019年之前的出版物上.
主要成果:
- 包括172份报告,CT成像比MRI使用频率更高;细分精度在模式之间相似.
- 队列大小和模型维度 (2D与3D) 并没有显著影响细分精度.
- 第三个腰椎水平是常用的,对体积分析有潜在的好处.
结论:
- 针对人体成分的自动软组织细分是一个动态的研究领域.
- 成像模式不会影响细分的准确性;体积分析可以提高弹性.
- 标准化数据集对于算法基准测试和临床采用至关重要.
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