Improving Automatic Melanoma Diagnosis Using Deep Learning-Based Segmentation of Irregular Networks

SIMPLE SUMMARY: Supervised deep learning techniques can now automatically process whole dermoscopic images and obtain a diagnostic accuracy for melanoma that exceeds that of specialists. These automatic diagnosis systems are now appearing in clinics. However, the computational techniques used cannot...

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Detalles Bibliográficos
Autores principales: Nambisan, Anand K., Maurya, Akanksha, Lama, Norsang, Phan, Thanh, Patel, Gehana, Miller, Keith, Lama, Binita, Hagerty, Jason, Stanley, Ronald, Stoecker, William V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9953766/
https://www.ncbi.nlm.nih.gov/pubmed/36831599
http://dx.doi.org/10.3390/cancers15041259

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9953766/
https://www.ncbi.nlm.nih.gov/pubmed/36831599
http://dx.doi.org/10.3390/cancers15041259

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