Radiomics in RayPlus: a Web-Based Tool for Texture Analysis in Medical Images.
Radiomics has been shown to have considerable potential and value in quantifying the tumor phenotype and predicting the treatment response. In most scenarios, the commercial and open-source software programs are available for quantitative analysis in medical images to streamline radiomics research....
| Publicado en: | Journal of Digital Imaging Vol. 32; no. 2; pp. 269 - 276 |
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| Autores principales: | , , , |
| Formato: | diagnostic images pictorial tables/charts Journal Article |
| Publicado: |
Springer Nature
Apr2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=135821482&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 135821482 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Apr2019 vid: 32 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 135821482 135821482 135821482 10.1007/s10278-018-0128-1 135821482 ppf: 269 ppct: 7 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Radiomics in RayPlus: a Web-Based Tool for Texture Analysis in Medical Images. aug: au: Yuan, Rong Shi, Shuyue Chen, Junhui Cheng, Guanxun affil: Department of Minimally Invasive Intervention, Peking University Shenzhen Hospital, Shenzhen PKU-HKUST Medical Center, Shenzhen, China sug: subj: Algorithms Image Processing, Computer Assisted World Wide Web Applications Software Design Neoplasms Radiography Phenotype Radiographic Image Interpretation, Computer-Assisted Internet Radiology Service Trends DICOM Collaboration ab: Radiomics has been shown to have considerable potential and value in quantifying the tumor phenotype and predicting the treatment response. In most scenarios, the commercial and open-source software programs are available for quantitative analysis in medical images to streamline radiomics research. However, at this stage, most of these programs are local applications and require users to have experience in programming and software engineering, which clinicians usually do not have. Therefore, in this article, a web-based tool was proposed to flexibly support radiomics research workflow tasks. Radiomics in RayPlus requires zero installation, is easy to maintain, and accessible anywhere via any PC or MAC with an Internet connection. The system provides functions including multimodality image import and viewing, ROI definition, feature extraction, and data sharing. As a web application, it appears an effective way to multi-institution and multi-department collaborative radiomics research and moreover, its transparency, flexibility, and portability can greatly accelerate the pace of clinical data analysis. pubtype: Academic Journal doctype: diagnostic images pictorial tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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