3D Slicer Craniomaxillofacial Modules Support Patient-Specific Decision-Making for Personalized Healthcare in Dental Research.

Jonas Bianchi, Beatriz Paniagua, Antonio Carlos De Oliveira Ruellas, Jean-Christophe Fillion-Robin, Juan C Prietro, João Roberto Gonçalves, James Hoctor, Marília Yatabe, Martin Styner, TengFei Li, Marcela Lima Gurgel, Cauby Maia Chaves, Camila Massaro, Daniela Gamba Garib, Lorena Vilanova, Jose Fernando Castanha Henriques, Aron Aliaga-Del Castillo, Guilherme Janson, Laura R Iwasaki, Jeffrey C Nickel, Karine Evangelista, Lucia Cevidanes
{"title":"3D Slicer Craniomaxillofacial Modules Support Patient-Specific Decision-Making for Personalized Healthcare in Dental Research.","authors":"Jonas Bianchi, Beatriz Paniagua, Antonio Carlos De Oliveira Ruellas, Jean-Christophe Fillion-Robin, Juan C Prietro, João Roberto Gonçalves, James Hoctor, Marília Yatabe, Martin Styner, TengFei Li, Marcela Lima Gurgel, Cauby Maia Chaves, Camila Massaro, Daniela Gamba Garib, Lorena Vilanova, Jose Fernando Castanha Henriques, Aron Aliaga-Del Castillo, Guilherme Janson, Laura R Iwasaki, Jeffrey C Nickel, Karine Evangelista, Lucia Cevidanes","doi":"10.1007/978-3-030-60946-7_5","DOIUrl":null,"url":null,"abstract":"<p><p>The biggest challenge to improve the diagnosis and therapies of Craniomaxillofacial conditions is to translate algorithms and software developments towards the creation of holistic patient models. A complete picture of the individual patient for treatment planning and personalized healthcare requires a compilation of clinician-friendly algorithms to provide minimally invasive diagnostic techniques with multimodal image integration and analysis. We describe here the implementation of the open-source Craniomaxillofacial module of the 3D Slicer software, as well as its clinical applications. This paper proposes data management approaches for multisource data extraction, registration, visualization, and quantification. These applications integrate medical images with clinical and biological data analytics, user studies, and other heterogeneous data.</p>","PeriodicalId":93218,"journal":{"name":"Multimodal learning for clinical decision support and clinical image-based procedures : 10th International Workshop, ML-CDS 2020, and 9th International Workshop, CLIP 2020, held in conjunction with MICCAI 2020, Lima, Peru, October 4-8, ...","volume":"12445 ","pages":"44-53"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7786614/pdf/nihms-1656400.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Multimodal learning for clinical decision support and clinical image-based procedures : 10th International Workshop, ML-CDS 2020, and 9th International Workshop, CLIP 2020, held in conjunction with MICCAI 2020, Lima, Peru, October 4-8, ...","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/978-3-030-60946-7_5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The biggest challenge to improve the diagnosis and therapies of Craniomaxillofacial conditions is to translate algorithms and software developments towards the creation of holistic patient models. A complete picture of the individual patient for treatment planning and personalized healthcare requires a compilation of clinician-friendly algorithms to provide minimally invasive diagnostic techniques with multimodal image integration and analysis. We describe here the implementation of the open-source Craniomaxillofacial module of the 3D Slicer software, as well as its clinical applications. This paper proposes data management approaches for multisource data extraction, registration, visualization, and quantification. These applications integrate medical images with clinical and biological data analytics, user studies, and other heterogeneous data.

三维颅颌面切片模块支持牙科研究中个性化医疗的特定患者决策。
要改进颅颌面疾病的诊断和治疗,最大的挑战是将算法和软件开发转化为创建患者整体模型。要为治疗计划和个性化医疗保健提供完整的患者个人图像,需要汇集便于临床医生使用的算法,以提供具有多模态图像集成和分析功能的微创诊断技术。我们在此介绍开源 3D Slicer 软件颅颌面模块的实施及其临床应用。本文提出了用于多源数据提取、配准、可视化和量化的数据管理方法。这些应用将医学图像与临床和生物数据分析、用户研究以及其他异构数据整合在一起。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信