Work

Learning to detect lymphocytes in immunohistochemistry with deep learning

Year: 2019

Type: article

Source: Medical Image Analysis

DOI: 10.1016/j.media.2019.101547

Authors: Zaneta Swiderska-Chadaj, Hans Pinckaers, Mart van Rijthoven, Maschenka Balkenhol, Margarita Melnikova, Oscar Geessink, Quirine Manson, Mark Sherman, Antonio Polonia, Jeremy Parry, Mustapha Abubakar, Geert Litjens, Jeroen van der Laak, Francesco Ciompi

Institutions: Radboud University Medical Center, Aarhus University, Regional Hospital Randers, University Medical Center Utrecht, Mayo Clinic, Mayo Clinic in Florida, Universidade do Porto, Fiona Stanley Hospital, National Cancer Institute, Division of Cancer Epidemiology and Genetics, Linköping University

Language: English

Topic: AI in cancer detection

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: bronze

Funders: European Commission, Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Radboud Universitair Medisch Centrum

Awards: G2802104974, G434337789, EXtreme-scale Analytics via Multimodal Ontology Discovery & Enhancement

OpenAlex ID: W2969657290

FWCI: 8.084

Cites: 48

Cited by: 163

Related to: 10