XNAT-PIC: Extending XNAT to Preclinical Imaging Centers.

Molecular imaging generates large volumes of heterogeneous biomedical imagery with an impelling need of guidelines for handling image data. Although several successful solutions have been implemented for human epidemiologic studies, few and limited approaches have been proposed for animal population...

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Publicado en:Journal of Digital Imaging Vol. 35; no. 4; pp. 860 - 876
Autores principales: Zullino, Sara, Paglialonga, Alessandro, Dastrù, Walter, Longo, Dario Livio, Aime, Silvio
Formato: diagnostic images pictorial tables/charts Journal Article
Publicado: Springer Nature Aug2022
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Aug2022
      vid: 35
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s10278-022-00612-z
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        atl: XNAT-PIC: Extending XNAT to Preclinical Imaging Centers.
      aug:
        au:
          Zullino, Sara
          Paglialonga, Alessandro
          Dastrù, Walter
          Longo, Dario Livio
          Aime, Silvio
        affil: Molecular Imaging Center, Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy
      sug:
        subj:
          Picture Archiving and Communication Systems
          Magnetic Resonance Imaging
          Image Processing, Computer Assisted
          Neuroradiography
          Database Construction
          Database Design
          Access to Information
          DICOM
          Molecular Imaging
          Software
          Digital Imaging
          Image Interpretation, Computer Assisted
      ab: Molecular imaging generates large volumes of heterogeneous biomedical imagery with an impelling need of guidelines for handling image data. Although several successful solutions have been implemented for human epidemiologic studies, few and limited approaches have been proposed for animal population studies. Preclinical imaging research deals with a variety of machinery yielding tons of raw data but the current practices to store and distribute image data are inadequate. Therefore, standard tools for the analysis of large image datasets need to be established. In this paper, we present an extension of XNAT for Preclinical Imaging Centers (XNAT-PIC). XNAT is a worldwide used, open-source platform for securely hosting, sharing, and processing of clinical imaging studies. Despite its success, neither tools for importing large, multimodal preclinical image datasets nor pipelines for processing whole imaging studies are yet available in XNAT. In order to overcome these limitations, we have developed several tools to expand the XNAT core functionalities for supporting preclinical imaging facilities. Our aim is to streamline the management and exchange of image data within the preclinical imaging community, thereby enhancing the reproducibility of the results of image processing and promoting open science practices.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        pictorial
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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