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

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

doi:10.21105/joss.07022

Review

Editor: @sappelhoff (all papers)
Reviewers: @PingjunChen (all reviews), @NetoPedro (all reviews)

Authors

Petros Liakopoulos (0009-0005-2015-6795), Julien Massonnet (0009-0004-9515-6100), Jonatan Bonjour (0009-0006-8165-6897), Medya Tekes Mizrakli, Simon Graham, Michel A. Cuendet, Amanda H. Seipel, Olivier Michielin, Doron Merkler, Andrew Janowczyk

Citation

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

@article{Liakopoulos2024, doi = {10.21105/joss.07022}, url = {https://doi.org/10.21105/joss.07022}, year = {2024}, publisher = {The Open Journal}, volume = {9}, number = {101}, pages = {7022}, author = {Petros Liakopoulos and Julien Massonnet and Jonatan Bonjour and Medya Tekes Mizrakli and Simon Graham and Michel A. Cuendet and Amanda H. Seipel and Olivier Michielin and Doron Merkler and Andrew Janowczyk}, title = {HoverFast: an accurate, high-throughput, clinically deployable nuclear segmentation tool for brightfield digital pathology images}, journal = {Journal of Open Source Software} }

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