[1]邓永锦,王朝阳,丘敏敏,等.基于平均密度投影影像的心脏表面运动全局模型的构建方法[J].中国医学物理学杂志,2025,42(2):199-207.[doi:DOI:10.3969/j.issn.1005-202X.2025.02.009]
　DENG Yongjin,WANG Zhaoyang,QIU Minmin,et al.Construction of a global model of cardiac surface motion based on average intensity projection image[J].Chinese Journal of Medical Physics,2025,42(2):199-207.[doi:DOI:10.3969/j.issn.1005-202X.2025.02.009]
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基于平均密度投影影像的心脏表面运动全局模型的构建方法()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
42
期数:
2025年第2期
页码:
199-207
栏目:
医学影像物理
出版日期:
2025-01-20

文章信息/Info

Title:
Construction of a global model of cardiac surface motion based on average intensity projection image
文章编号:
1005-202X（2025）02-0199-09
作者:
邓永锦; 王朝阳; 丘敏敏; 黄剑文
中山大学附属第一医院放射治疗科， 广东 广州 510080
Author(s):
DENG Yongjin;  WANG Zhaoyang;  QIU Minmin;  HUANG Jianwen
Department of Radiation Oncology, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou 510080, China
关键词:
心脏; 平均密度投影; 心脏表面运动; 主要成分分析; 点云
Keywords:
Keywords: cardiac average intensity projection cardiac surface motion principal component analysis point cloud
分类号:
R318；R563.9
DOI:
DOI:10.3969/j.issn.1005-202X.2025.02.009
文献标志码:
A
摘要:
目的：构建一种基于平均密度投影（AIP）影像的心脏表面运动全局模型。方法：将核磁共振心电触发电影的影像数据分为训练集和测试集，进行模型的构建和验证。在AIP影像表面点云上获取基准点，通过曲面特征法确定各时相表面点云对应点。采用主成分分析算法提取特征信息，建立基准点和对应点间的映射关系，构建从AIP表面点云预测各时相表面点云的模型。结果：测试集上模型对应点预测误差RMSE为（0.209±0.020） mm~（0.841±0.074） mm，而各时相表面点云预测误差欧式距离为（1.399±0.029） mm~（1.658±0.100） mm。结论：本文提出的全局模型准确性较高，可为图像分割和临床治疗提供参考。
Abstract:
Abstract: Objective To construct a global model of cardiac surface motion based on average intensity projection (AIP) image. Methods The cine magnetic resonance imaging data were divided into training set and test set for model construction and validation. The datum points were obtained on the AIP surface point cloud, and the corresponding points of each cardiac phase surface point cloud were found based on surface features. Principal component analysis was used to extract feature information, establish the mapping relationship between the datum points and the corresponding points, and construct a model for predicting each temporal phase surface point cloud from the AIP surface point cloud. Results The RMSE of the model on test set for corresponding point prediction ranged from (0.209±0.020) mm to (0.841±0.074) mm, while the Euclidean distance for each time phase surface point cloud prediction ranged from (1.399±0.029) mm to (1.658±0.100) mm. Conclusion The proposed global model exhibit high accuracy and can provide a reference for image segmentation and clinical treatments.

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备注/Memo

备注/Memo:
【收稿日期】2024-08-16 【基金项目】广东省医学科研基金（A2024011） 【作者简介】邓永锦，工程师，研究方向：放疗剂量的精确性，E-mail: dengyj27@mail.sysu.edu.cn 【通信作者】黄剑文，主管技师，研究方向：放疗定位的精确性，E-mail: huangjw77@mail.sysu.edu.cn
更新日期/Last Update: 2025-01-22