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Integrating the OHIF Viewer into XNAT: Achievements, Challenges and Prospects for Quantitative Imaging Studies.
Doran, Simon J; Al Sa'd, Mohammad; Petts, James A; Darcy, James; Alpert, Kate; Cho, Woonchan; Sanchez, Lorena Escudero; Alle, Sachidanand; El Harouni, Ahmed; Genereaux, Brad; Ziegler, Erik; Harris, Gordon J; Aboagye, Eric O; Sala, Evis; Koh, Dow-Mu; Marcus, Dan.
Afiliación
  • Doran SJ; Division of Radiotherapy and Imaging, Institute of Cancer Research, 15 Cotswold Rd, London SM2 5NG, UK.
  • Al Sa'd M; CRUK National Cancer Imaging Translational Accelerator, UK.
  • Petts JA; CRUK National Cancer Imaging Translational Accelerator, UK.
  • Darcy J; Cancer Imaging Centre, Department of Surgery & Cancer, Imperial College, London SW7 2AZ, UK.
  • Alpert K; Ovela Solutions Ltd., 20-22 Wenlock Road, London N1 7GU, UK.
  • Cho W; Division of Radiotherapy and Imaging, Institute of Cancer Research, 15 Cotswold Rd, London SM2 5NG, UK.
  • Sanchez LE; CRUK National Cancer Imaging Translational Accelerator, UK.
  • Alle S; Flywheel LLC, 1015 Glenwood Ave, Suite 300, Minneapolis, MN 55405, USA.
  • El Harouni A; Neuroimaging Informatics Analysis Center, Washington University School of Medicine, 660 S Euclid Ave, St. Louis, MO 63110, USA.
  • Genereaux B; CRUK National Cancer Imaging Translational Accelerator, UK.
  • Ziegler E; Department of Radiology, University of Cambridge, Hills Rd, Cambridge CB2 0QQ, UK.
  • Harris GJ; Cancer Research UK Cambridge Centre, University of Cambridge Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK.
  • Aboagye EO; NVIDIA, 2788 San Tomas Expressway, Santa Clara, CA 95051, USA.
  • Sala E; NVIDIA, 2788 San Tomas Expressway, Santa Clara, CA 95051, USA.
  • Koh DM; NVIDIA, 2788 San Tomas Expressway, Santa Clara, CA 95051, USA.
  • Marcus D; Open Health Imaging Foundation, Massachusetts General Hospital, 55 Fruit St., Boston, MA 02114, USA.
Tomography ; 8(1): 497-512, 2022 02 11.
Article en En | MEDLINE | ID: mdl-35202205
ABSTRACT

Purpose:

XNAT is an informatics software platform to support imaging research, particularly in the context of large, multicentre studies of the type that are essential to validate quantitative imaging biomarkers. XNAT provides import, archiving, processing and secure distribution facilities for image and related study data. Until recently, however, modern data visualisation and annotation tools were lacking on the XNAT platform. We describe the background to, and implementation of, an integration of the Open Health Imaging Foundation (OHIF) Viewer into the XNAT environment. We explain the challenges overcome and discuss future prospects for quantitative imaging studies. Materials and

methods:

The OHIF Viewer adopts an approach based on the DICOM web protocol. To allow operation in an XNAT environment, a data-routing methodology was developed to overcome the mismatch between the DICOM and XNAT information models and a custom viewer panel created to allow navigation within the viewer between different XNAT projects, subjects and imaging sessions. Modifications to the development environment were made to allow developers to test new code more easily against a live XNAT instance. Major new developments focused on the creation and storage of regions-of-interest (ROIs) and included ROI creation and editing tools for both contour- and mask-based regions; a "smart CT" paintbrush tool; the integration of NVIDIA's Artificial Intelligence Assisted Annotation (AIAA); the ability to view surface meshes, fractional segmentation maps and image overlays; and a rapid image reader tool aimed at radiologists. We have incorporated the OHIF microscopy extension and, in parallel, introduced support for microscopy session types within XNAT for the first time.

Results:

Integration of the OHIF Viewer within XNAT has been highly successful and numerous additional and enhanced tools have been created in a programme started in 2017 that is still ongoing. The software has been downloaded more than 3700 times during the course of the development work reported here, demonstrating the impact of the work.

Conclusions:

The OHIF open-source, zero-footprint web viewer has been incorporated into the XNAT platform and is now used at many institutions worldwide. Further innovations are envisaged in the near future.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Inteligencia Artificial / Diagnóstico por Imagen Tipo de estudio: Diagnostic_studies Límite: Humans Idioma: En Revista: Tomography Año: 2022 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Inteligencia Artificial / Diagnóstico por Imagen Tipo de estudio: Diagnostic_studies Límite: Humans Idioma: En Revista: Tomography Año: 2022 Tipo del documento: Article País de afiliación: Reino Unido