Deep learning-based spatial immunoprofiling of multiplex immunofluorescence images distinguishes tuberculosis disease states in diversity outbred mice

• Usama Sajjad ,

  Roles Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft

  * E-mail: Usama.Sajjad@osumc.edu

  Affiliation Department of Pathology, The Ohio State University Wexner Medical Center, Columbus, Ohio, United States of America

  https://orcid.org/0000-0002-7262-3034

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• Nicholas A. Crossland,

  Roles Data curation, Validation, Writing – review & editing

  Affiliations National Emerging Infectious Diseases Laboratories (NEIDL), Boston University, Boston, Massachusetts, United States of America, Department of Pathology and Laboratory Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts, United States of America, Department of Virology, Immunology, & Microbiology, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts, United States of America

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• Metin N. Gurcan,

  Roles Conceptualization, Investigation, Supervision, Validation, Writing – review & editing

  Affiliation Center for Artificial Intelligence Research, Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America

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• Gillian Beamer,

  Roles Conceptualization, Funding acquisition, Project administration, Supervision, Validation, Writing – review & editing

  Affiliation Population Health, Texas Biomedical Research Institute, San Antonio, Texas, United States of America

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• Muhammad Khalid Khan Niazi

  Roles Funding acquisition, Investigation, Project administration, Resources, Software, Supervision, Writing – review & editing

  Affiliation Department of Pathology, The Ohio State University Wexner Medical Center, Columbus, Ohio, United States of America

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