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tranSMART-XNAT Connector tranSMART-XNAT connector-image selection based on clinical phenotypes and genetic profiles.
He, Sijin; Yong, May; Matthews, Paul M; Guo, Yike.
Afiliación
  • He S; European Bioinformatics Institute, Cambridge, UK.
  • Yong M; Data Science Institute, Imperial College London, London, UK.
  • Matthews PM; Division of Brain Sciences, Imperial College London, London, UK.
  • Guo Y; Data Science Institute, Imperial College London, London, UK.
Bioinformatics ; 33(5): 787-788, 2017 03 01.
Article en En | MEDLINE | ID: mdl-28025201
ABSTRACT
Motivation TranSMART has a wide range of functionalities for translational research and a large user community, but it does not support imaging data. In this context, imaging data typically includes 2D or 3D sets of magnitude data and metadata information. Imaging data may summarise complex feature descriptions in a less biased fashion than user defined plain texts and numeric numbers. Imaging data also is contextualised by other data sets and may be analysed jointly with other data that can explain features or their variation.

Results:

Here we describe the tranSMART-XNAT Connector we have developed. This connector consists of components for data capture, organisation and analysis. Data capture is responsible for imaging capture either from PACS system or directly from an MRI scanner, or from raw data files. Data are organised in a similar fashion as tranSMART and are stored in a format that allows direct analysis within tranSMART. The connector enables selection and download of DICOM images and associated resources using subjects' clinical phenotypic and genotypic criteria. Availability and Implementation tranSMART-XNAT connector is written in Java/Groovy/Grails. It is maintained and available for download at https//github.com/sh107/transmart-xnat-connector.git. Contact sijin@ebi.ac.uk.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Programas Informáticos / Almacenamiento y Recuperación de la Información / Biología Computacional Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2017 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Programas Informáticos / Almacenamiento y Recuperación de la Información / Biología Computacional Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2017 Tipo del documento: Article País de afiliación: Reino Unido