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On image search in histopathology.
Tizhoosh, H R; Pantanowitz, Liron.
Afiliação
  • Tizhoosh HR; Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, USA.
  • Pantanowitz L; Department of Pathology, School of Medicine, University of Pittsburgh, PA, USA.
J Pathol Inform ; 15: 100375, 2024 Dec.
Article em En | MEDLINE | ID: mdl-38645985
ABSTRACT
Pathology images of histopathology can be acquired from camera-mounted microscopes or whole-slide scanners. Utilizing similarity calculations to match patients based on these images holds significant potential in research and clinical contexts. Recent advancements in search technologies allow for implicit quantification of tissue morphology across diverse primary sites, facilitating comparisons, and enabling inferences about diagnosis, and potentially prognosis, and predictions for new patients when compared against a curated database of diagnosed and treated cases. In this article, we comprehensively review the latest developments in image search technologies for histopathology, offering a concise overview tailored for computational pathology researchers seeking effective, fast, and efficient image search methods in their work.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: J Pathol Inform Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: J Pathol Inform Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos