O1 Abstract
Differentiating Malignant from Benign for Melanocytic and Non-melanocytic Skin Tumors : A Pilot Study on Hyperspectral Imaging and Convolutional Neural Networks (2022)

Lindholm, V., Raita-Hakola, A.-M., Annala, L., Salmivuori, M., Jeskanen, L., Koskenmies, S., Pitkänen, S., Saari, H., Pölönen, I., Isoherranen, K., & Ranki, A. (2022). Differentiating Malignant from Benign for Melanocytic and Non-melanocytic Skin Tumors : A Pilot Study on Hyperspectral Imaging and Convolutional Neural Networks. In Abstracts from 35th Congress of Nordic Dermatology and Venereology (pp. 51). Society for Publication of Acta Dermato-Venereologica. Acta Dermato-Venereologica, Suppl 222. https://medicaljournalssweden.se/actadv/issue/view/159

JYU authors or editors

Publication details

All authors or editors: Lindholm, Vivian; Raita-Hakola, Anna-Maria; Annala, Leevi; Salmivuori, Mari; Jeskanen, Leila; Koskenmies, Sari; Pitkänen, Sari; Saari, Heikki; Pölönen, Ilkka; Isoherranen, Kirsi; et al.

Parent publication: Abstracts from 35th Congress of Nordic Dermatology and Venereology

Place and date of conference: Copenhagen, Denmark, 19.-22.2022

Journal or series: Acta Dermato-Venereologica

ISSN: 0001-5555

eISSN: 1651-2057

Publication year: 2022

Number in series: Suppl 222

Pages range: 51

Number of pages in the book: 56

Publisher: Society for Publication of Acta Dermato-Venereologica

Publication country: Sweden

Publication language: English

Persistent website address: https://medicaljournalssweden.se/actadv/issue/view/159

Publication open access: Openly available

Publication channel open access: Open Access channel

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/82488

Keywords: skin cancer; melanoma; basal cell carcinoma; carcinomas; diagnostics; hyperspectral imaging; machine learning; neural networks (information technology)

Contributing organizations

Ministry reporting: Won't be reported