注意:传统细分方法的缺陷来自磁共振成像脑扫描,用于在患有病理的儿童中进行三维表面建模
Anith Chacko1, Sean Schoeman2, Shyam Sunder B Venkatakrishna2
1CRICBristol, 60 St Michael's Hill, Faculty of Health Sciences, University of Bristol, Bristol, BS28DX, UK. anithchacko@gmail.com.
Pediatric radiology
|May 30, 2023
概括
自动化大脑细分工具与异常的儿科MRI扫描作斗争,特别是那些有空洞的MRI扫描. 复杂的病理需要精细的方法.
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
- 儿科放射学 儿科放射学
背景情况:
- 自动细分工具对于分析大脑磁共振扫描 (MR) 非常重要.
- 评估这些工具对异常儿科脑部扫描的性能对于临床应用至关重要.
研究的目的:
- 评估常见的自动化细分工具在异常儿科MRI脑部扫描上的适应性.
- 确定当前工具在细分复杂的大脑病理方面的局限性.
主要方法:
- 三十五个儿科的MRI脑部扫描被按病理分类:正常,缩,腔腔和其他.
- 三种工具 (CAT12,SPM12,MRTool) 使用默认和调整的设置进行了测试.
- 放射学家的共识决定了基于表面精度的成功.
主要成果:
- 自动细分在严重表面大脑病理的扫描中失败了.
- "空洞"组的细分显示了较低的成功率:23.1% (CAT12),69.2% (SPM12) 和46.2% (MRTool).
- 性能问题即使在精细的设置和手动编辑中仍然存在.
结论:
- 目前的自动化细分工具对儿童脑部MRI扫描异常的适应能力有限,特别是在腔等复杂病理方面.
- 需要进一步的研究来增强儿童神经成像的自动化细分工作流.
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