胸部 CT 图像与辐射诱发肺部疾病的纵向配准:基于分量结构的分而治之法,利用相干点漂移进行明智配准

IF 4.9 2区 医学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computer methods and programs in biomedicine Pub Date : 2024-08-28 DOI:10.1016/j.cmpb.2024.108401
{"title":"胸部 CT 图像与辐射诱发肺部疾病的纵向配准:基于分量结构的分而治之法,利用相干点漂移进行明智配准","authors":"","doi":"10.1016/j.cmpb.2024.108401","DOIUrl":null,"url":null,"abstract":"<div><h3>Background and Objective</h3><p>Registration of pulmonary computed tomography (CT) images with radiation-induced lung diseases (RILD) was essential to investigate the voxel-wise relationship between the formation of RILD and the radiation dose received by different tissues. Although various approaches had been developed for the registration of lung CTs, their performances remained clinically unsatisfactory for registration of lung CT images with RILD. The main difficulties arose from the longitudinal change in lung parenchyma, including RILD and volumetric change of lung cancers, after radiation therapy, leading to inaccurate registration and artifacts caused by erroneous matching of the RILD tissues.</p></div><div><h3>Methods</h3><p>To overcome the influence of the parenchymal changes, a divide-and-conquer approach rooted in the coherent point drift (CPD) paradigm was proposed. The proposed method was based on two kernel ideas. One was the idea of component structure wise registration. Specifically, the proposed method relaxed the intrinsic assumption of equal isotropic covariances in CPD by decomposing a lung and its surrounding tissues into component structures and independently registering the component structures pairwise by CPD. The other was the idea of defining a vascular subtree centered at a matched branch point as a component structure. This idea could not only provide a sufficient number of matched feature points within a parenchyma, but avoid being corrupted by the false feature points resided in the RILD tissues due to globally and indiscriminately sampling using mathematical operators. The overall deformation model was built by using the Thin Plate Spline based on all matched points.</p></div><div><h3>Results</h3><p>This study recruited 30 pairs of lung CT images with RILD, 15 of which were used for internal validation (leave-one-out cross-validation) and the other 15 for external validation. The experimental results showed that the proposed algorithm achieved a mean and a mean of maximum 1 % of average surface distances &lt;2 and 8 mm, respectively, and a mean and a maximum target registration error &lt;2 mm and 5 mm on both internal and external validation datasets. The paired two-sample <em>t</em>-tests corroborated that the proposed algorithm outperformed a recent method, the Stavropoulou's method, on the external validation dataset (<em>p</em> &lt; 0.05).</p></div><div><h3>Conclusions</h3><p>The proposed algorithm effectively reduced the influence of parenchymal changes, resulting in a reasonably accurate and artifact-free registration.</p></div>","PeriodicalId":10624,"journal":{"name":"Computer methods and programs in biomedicine","volume":null,"pages":null},"PeriodicalIF":4.9000,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Longitudinal registration of thoracic CT images with radiation-induced lung diseases: A divide-and-conquer approach based on component structure wise registration using coherent point drift\",\"authors\":\"\",\"doi\":\"10.1016/j.cmpb.2024.108401\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background and Objective</h3><p>Registration of pulmonary computed tomography (CT) images with radiation-induced lung diseases (RILD) was essential to investigate the voxel-wise relationship between the formation of RILD and the radiation dose received by different tissues. Although various approaches had been developed for the registration of lung CTs, their performances remained clinically unsatisfactory for registration of lung CT images with RILD. The main difficulties arose from the longitudinal change in lung parenchyma, including RILD and volumetric change of lung cancers, after radiation therapy, leading to inaccurate registration and artifacts caused by erroneous matching of the RILD tissues.</p></div><div><h3>Methods</h3><p>To overcome the influence of the parenchymal changes, a divide-and-conquer approach rooted in the coherent point drift (CPD) paradigm was proposed. The proposed method was based on two kernel ideas. One was the idea of component structure wise registration. Specifically, the proposed method relaxed the intrinsic assumption of equal isotropic covariances in CPD by decomposing a lung and its surrounding tissues into component structures and independently registering the component structures pairwise by CPD. The other was the idea of defining a vascular subtree centered at a matched branch point as a component structure. This idea could not only provide a sufficient number of matched feature points within a parenchyma, but avoid being corrupted by the false feature points resided in the RILD tissues due to globally and indiscriminately sampling using mathematical operators. The overall deformation model was built by using the Thin Plate Spline based on all matched points.</p></div><div><h3>Results</h3><p>This study recruited 30 pairs of lung CT images with RILD, 15 of which were used for internal validation (leave-one-out cross-validation) and the other 15 for external validation. The experimental results showed that the proposed algorithm achieved a mean and a mean of maximum 1 % of average surface distances &lt;2 and 8 mm, respectively, and a mean and a maximum target registration error &lt;2 mm and 5 mm on both internal and external validation datasets. The paired two-sample <em>t</em>-tests corroborated that the proposed algorithm outperformed a recent method, the Stavropoulou's method, on the external validation dataset (<em>p</em> &lt; 0.05).</p></div><div><h3>Conclusions</h3><p>The proposed algorithm effectively reduced the influence of parenchymal changes, resulting in a reasonably accurate and artifact-free registration.</p></div>\",\"PeriodicalId\":10624,\"journal\":{\"name\":\"Computer methods and programs in biomedicine\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.9000,\"publicationDate\":\"2024-08-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer methods and programs in biomedicine\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0169260724003948\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer methods and programs in biomedicine","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0169260724003948","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

摘要

背景和目的对肺部计算机断层扫描(CT)图像与辐射诱发的肺部疾病(RILD)进行配准,对于研究 RILD 的形成与不同组织所受辐射剂量之间的体素关系至关重要。尽管已开发出多种肺部 CT 图像配准方法,但在临床上,这些方法在配准有 RILD 的肺部 CT 图像时的表现仍不尽如人意。主要的困难来自于放疗后肺实质的纵向变化,包括 RILD 和肺癌的体积变化,从而导致 RILD 组织匹配错误造成的配准不准确和伪影。该方法基于两个核心思想。其一是成分结构明智配准的思想。具体来说,该方法通过将肺及其周围组织分解为组件结构,并通过 CPD 对组件结构进行独立配对,放宽了 CPD 中各向同性协方差相等的固有假设。另一种方法是将以匹配分支点为中心的血管子树定义为一个成分结构。这一想法不仅能在实质组织内提供足够数量的匹配特征点,还能避免因使用数学运算符进行全局无差别采样而被 RILD 组织中的虚假特征点所干扰。结果本研究共收集了 30 对带有 RILD 的肺部 CT 图像,其中 15 对用于内部验证(leave-one-out cross-validation),另外 15 对用于外部验证。实验结果表明,所提出的算法在内部和外部验证数据集上的平均表面距离分别为 2 毫米和 8 毫米,平均和最大目标配准误差分别为 2 毫米和 5 毫米。成对双样本 t 检验证实,在外部验证数据集上,所提出的算法优于最近的一种方法,即 Stavropoulou 方法(p < 0.05)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Longitudinal registration of thoracic CT images with radiation-induced lung diseases: A divide-and-conquer approach based on component structure wise registration using coherent point drift

Background and Objective

Registration of pulmonary computed tomography (CT) images with radiation-induced lung diseases (RILD) was essential to investigate the voxel-wise relationship between the formation of RILD and the radiation dose received by different tissues. Although various approaches had been developed for the registration of lung CTs, their performances remained clinically unsatisfactory for registration of lung CT images with RILD. The main difficulties arose from the longitudinal change in lung parenchyma, including RILD and volumetric change of lung cancers, after radiation therapy, leading to inaccurate registration and artifacts caused by erroneous matching of the RILD tissues.

Methods

To overcome the influence of the parenchymal changes, a divide-and-conquer approach rooted in the coherent point drift (CPD) paradigm was proposed. The proposed method was based on two kernel ideas. One was the idea of component structure wise registration. Specifically, the proposed method relaxed the intrinsic assumption of equal isotropic covariances in CPD by decomposing a lung and its surrounding tissues into component structures and independently registering the component structures pairwise by CPD. The other was the idea of defining a vascular subtree centered at a matched branch point as a component structure. This idea could not only provide a sufficient number of matched feature points within a parenchyma, but avoid being corrupted by the false feature points resided in the RILD tissues due to globally and indiscriminately sampling using mathematical operators. The overall deformation model was built by using the Thin Plate Spline based on all matched points.

Results

This study recruited 30 pairs of lung CT images with RILD, 15 of which were used for internal validation (leave-one-out cross-validation) and the other 15 for external validation. The experimental results showed that the proposed algorithm achieved a mean and a mean of maximum 1 % of average surface distances <2 and 8 mm, respectively, and a mean and a maximum target registration error <2 mm and 5 mm on both internal and external validation datasets. The paired two-sample t-tests corroborated that the proposed algorithm outperformed a recent method, the Stavropoulou's method, on the external validation dataset (p < 0.05).

Conclusions

The proposed algorithm effectively reduced the influence of parenchymal changes, resulting in a reasonably accurate and artifact-free registration.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Computer methods and programs in biomedicine
Computer methods and programs in biomedicine 工程技术-工程:生物医学
CiteScore
12.30
自引率
6.60%
发文量
601
审稿时长
135 days
期刊介绍: To encourage the development of formal computing methods, and their application in biomedical research and medical practice, by illustration of fundamental principles in biomedical informatics research; to stimulate basic research into application software design; to report the state of research of biomedical information processing projects; to report new computer methodologies applied in biomedical areas; the eventual distribution of demonstrable software to avoid duplication of effort; to provide a forum for discussion and improvement of existing software; to optimize contact between national organizations and regional user groups by promoting an international exchange of information on formal methods, standards and software in biomedicine. Computer Methods and Programs in Biomedicine covers computing methodology and software systems derived from computing science for implementation in all aspects of biomedical research and medical practice. It is designed to serve: biochemists; biologists; geneticists; immunologists; neuroscientists; pharmacologists; toxicologists; clinicians; epidemiologists; psychiatrists; psychologists; cardiologists; chemists; (radio)physicists; computer scientists; programmers and systems analysts; biomedical, clinical, electrical and other engineers; teachers of medical informatics and users of educational software.
期刊最新文献
Thrombogenic Risk Assessment of Transcatheter Prosthetic Heart Valves Using a Fluid-Structure Interaction Approach The role of TandemHeartTM combined with ProtekDuoTM as right ventricular support device: A simulation approach The CrowdGleason dataset: Learning the Gleason grade from crowds and experts. Discovering explainable biomarkers for breast cancer anti-PD1 response via network Shapley value analysis. Data-driven reduced order surrogate modeling for coronary in-stent restenosis.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1