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HoverFast: an accurate, high-throughput, clinically deployable nuclear segmentation tool for brightfield digital pathology images

Year: 2024

Type: article

Abstract: Liakopoulos et al., (2024). HoverFast: an accurate, high-throughput, clinically deployable nuclear segmentation tool for brightfield digital pathology images. Journal of Open Source Software, 9(101), 7022, https://doi.org/10.21105/joss.07022

Source: The Journal of Open Source Software

DOI: 10.21105/joss.07022

Authors: Petros Liakopoulos, Julien Massonnet, Jonatan Bonjour, Medya Tekes Mizrakli, Simon Graham, Michel A. Cuendet, Amanda H. Seipel, Olivier Michielin, Doron Merkler, Andrew Janowczyk

Institutions: University of Geneva, University Hospital of Geneva, École Polytechnique Fédérale de Lausanne, Histofy Ltd. (United Kingdom)

Language: English

Topic: AI in cancer detection

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4402864401

FWCI: 0.444

Cites: 13

Cited by: 3

Related to: 10