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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

Texto completo: 1 Colección: 01-internacional Base 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 Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base 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 Pais de publicación: Suiza