Computer-assisted mitotic count using a deep learning–based algorithm improves interobserver reproducibility and accuracy

The mitotic count (MC) is an important histological parameter for prognostication of malignant neoplasms. However, it has inter- and intraobserver discrepancies due to difficulties in selecting the region of interest (MC-ROI) and in identifying or classifying mitotic figures (MFs). Recent progress i...

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Detalles Bibliográficos
Autores principales: Bertram, Christof A., Aubreville, Marc, Donovan, Taryn A., Bartel, Alexander, Wilm, Frauke, Marzahl, Christian, Assenmacher, Charles-Antoine, Becker, Kathrin, Bennett, Mark, Corner, Sarah, Cossic, Brieuc, Denk, Daniela, Dettwiler, Martina, Gonzalez, Beatriz Garcia, Gurtner, Corinne, Haverkamp, Ann-Kathrin, Heier, Annabelle, Lehmbecker, Annika, Merz, Sophie, Noland, Erica L., Plog, Stephanie, Schmidt, Anja, Sebastian, Franziska, Sledge, Dodd G., Smedley, Rebecca C., Tecilla, Marco, Thaiwong, Tuddow, Fuchs-Baumgartinger, Andrea, Meuten, Donald J., Breininger, Katharina, Kiupel, Matti, Maier, Andreas, Klopfleisch, Robert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8928234/
https://www.ncbi.nlm.nih.gov/pubmed/34965805
http://dx.doi.org/10.1177/03009858211067478

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8928234/
https://www.ncbi.nlm.nih.gov/pubmed/34965805
http://dx.doi.org/10.1177/03009858211067478

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