{"title":"利用扩散磁共振成像实现三维主要白质束的自动分割","authors":"Christina Andica, Koji Kamagata, Shigeki Aoki","doi":"10.1007/s12565-023-00715-9","DOIUrl":null,"url":null,"abstract":"<div><p>White matter bundle segmentation using diffusion magnetic resonance imaging fiber tractography enables detailed evaluation of individual white matter tracts three-dimensionally, and plays a crucial role in studying human brain anatomy, function, development, and diseases. Manual extraction of streamlines utilizing a combination of the inclusion and exclusion of regions of interest can be considered the current gold standard for extracting white matter bundles from whole-brain tractograms. However, this is a time-consuming and operator-dependent process with limited reproducibility. Several automated approaches using different strategies to reconstruct the white matter tracts have been proposed to address the issues of time, labor, and reproducibility. In this review, we discuss few of the most well-validated approaches that automate white matter bundle segmentation with an end-to-end pipeline, including TRActs Constrained by UnderLying Anatomy (TRACULA), Automated Fiber Quantification, and TractSeg.</p></div>","PeriodicalId":7816,"journal":{"name":"Anatomical Science International","volume":"98 3","pages":"318 - 336"},"PeriodicalIF":1.2000,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s12565-023-00715-9.pdf","citationCount":"3","resultStr":"{\"title\":\"Automated three-dimensional major white matter bundle segmentation using diffusion magnetic resonance imaging\",\"authors\":\"Christina Andica, Koji Kamagata, Shigeki Aoki\",\"doi\":\"10.1007/s12565-023-00715-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>White matter bundle segmentation using diffusion magnetic resonance imaging fiber tractography enables detailed evaluation of individual white matter tracts three-dimensionally, and plays a crucial role in studying human brain anatomy, function, development, and diseases. Manual extraction of streamlines utilizing a combination of the inclusion and exclusion of regions of interest can be considered the current gold standard for extracting white matter bundles from whole-brain tractograms. However, this is a time-consuming and operator-dependent process with limited reproducibility. Several automated approaches using different strategies to reconstruct the white matter tracts have been proposed to address the issues of time, labor, and reproducibility. In this review, we discuss few of the most well-validated approaches that automate white matter bundle segmentation with an end-to-end pipeline, including TRActs Constrained by UnderLying Anatomy (TRACULA), Automated Fiber Quantification, and TractSeg.</p></div>\",\"PeriodicalId\":7816,\"journal\":{\"name\":\"Anatomical Science International\",\"volume\":\"98 3\",\"pages\":\"318 - 336\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2023-04-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s12565-023-00715-9.pdf\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Anatomical Science International\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s12565-023-00715-9\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ANATOMY & MORPHOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Anatomical Science International","FirstCategoryId":"3","ListUrlMain":"https://link.springer.com/article/10.1007/s12565-023-00715-9","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ANATOMY & MORPHOLOGY","Score":null,"Total":0}
Automated three-dimensional major white matter bundle segmentation using diffusion magnetic resonance imaging
White matter bundle segmentation using diffusion magnetic resonance imaging fiber tractography enables detailed evaluation of individual white matter tracts three-dimensionally, and plays a crucial role in studying human brain anatomy, function, development, and diseases. Manual extraction of streamlines utilizing a combination of the inclusion and exclusion of regions of interest can be considered the current gold standard for extracting white matter bundles from whole-brain tractograms. However, this is a time-consuming and operator-dependent process with limited reproducibility. Several automated approaches using different strategies to reconstruct the white matter tracts have been proposed to address the issues of time, labor, and reproducibility. In this review, we discuss few of the most well-validated approaches that automate white matter bundle segmentation with an end-to-end pipeline, including TRActs Constrained by UnderLying Anatomy (TRACULA), Automated Fiber Quantification, and TractSeg.
期刊介绍:
The official English journal of the Japanese Association of Anatomists, Anatomical Science International (formerly titled Kaibogaku Zasshi) publishes original research articles dealing with morphological sciences.
Coverage in the journal includes molecular, cellular, histological and gross anatomical studies on humans and on normal and experimental animals, as well as functional morphological, biochemical, physiological and behavioral studies if they include morphological analysis.