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IMC-Denoise: a content aware denoising pipeline to enhance Imaging Mass Cytometry.
Lu, Peng; Oetjen, Karolyn A; Bender, Diane E; Ruzinova, Marianna B; Fisher, Daniel A C; Shim, Kevin G; Pachynski, Russell K; Brennen, W Nathaniel; Oh, Stephen T; Link, Daniel C; Thorek, Daniel L J.
Afiliación
  • Lu P; Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, USA.
  • Oetjen KA; Department of Radiology, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, USA.
  • Bender DE; Program in Quantitative Molecular Therapeutics, Washington University School of Medicine, St. Louis, USA.
  • Ruzinova MB; Department of Medicine, Washington University School of Medicine, St. Louis, USA.
  • Fisher DAC; The Bursky Center for Human Immunology and Immunotherapy Programs Immunomonitoring Laboratory, Washington University School of Medicine, St. Louis, USA.
  • Shim KG; Department of Pathology & Immunology, Washington University School of Medicine, St. Louis, USA.
  • Pachynski RK; Department of Medicine, Washington University School of Medicine, St. Louis, USA.
  • Brennen WN; Department of Medicine, Washington University School of Medicine, St. Louis, USA.
  • Oh ST; Department of Medicine, Washington University School of Medicine, St. Louis, USA.
  • Link DC; Department of Oncology, Sidney Kimmel Comprehensive Cancer Center (SKCCC), Johns Hopkins University, Baltimore, USA.
  • Thorek DLJ; Department of Urology, James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, USA.
Nat Commun ; 14(1): 1601, 2023 03 23.
Article en En | MEDLINE | ID: mdl-36959190
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Tomografía Computarizada por Rayos X Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Nat Commun Asunto de la revista: BIOLOGIA / CIENCIA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Tomografía Computarizada por Rayos X Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Nat Commun Asunto de la revista: BIOLOGIA / CIENCIA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido