HoverFast: an accurate, high-throughput, clinicallydeployable nuclear segmentation tool for brightfield digital pathologyimages
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
Authors
- Olivier Michielin (ORCID: https://orcid.org/0000-0003-4926-6355)
- Simon Graham (ORCID: https://orcid.org/0000-0002-2214-8212)
- Andrew Janowczyk (ORCID: https://orcid.org/0000-0003-2982-4321)
- Doron Merkler (ORCID: https://orcid.org/0000-0002-0247-2007)
- Michel A. Cuendet (ORCID: https://orcid.org/0000-0002-0754-3425)
- Petros Liakopoulos (ORCID: https://orcid.org/0009-0005-2015-6795)
- Julien Massonnet (ORCID: https://orcid.org/0009-0004-9515-6100)
- Medya Tekes Mizrakli
- Amanda H. Seipel
- Jonatan Bonjour (ORCID: https://orcid.org/0009-0006-8165-6897)
Publication Details
- Journal
- The Journal of Open Source Software
- Published
- 2024-09-26
- DOI
- https://doi.org/10.21105/joss.07022
- Citations
- 2
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.69