Convolutional neural networks in skin cancer detection using spatial and spectral domain

Ilkka Pölönen; Samuli Rahkonen; Leevi Annala; Noora Neittaanmäki

doi:10.1117/12.2509871

26 February 2019 Convolutional neural networks in skin cancer detection using spatial and spectral domain

Ilkka Pölönen, Samuli Rahkonen, Leevi Annala, Noora Neittaanmäki

Proceedings Volume 10851, Photonics in Dermatology and Plastic Surgery 2019; 108510B (2019) https://doi.org/10.1117/12.2509871
Event: SPIE BiOS, 2019, San Francisco, California, United States

Abstract

Skin cancers are a world wide deathly health problem, where significant life and cost savings could be achieved if detection of cancer can be done in early phase. Hypespectral imaging is prominent tool for non-invasive screening. In this study we compare how use of both spectral and spatial domain increase classification performance of convolutional neural networks. We compare five different neural network architectures for real patient data. Our models gain same or slightly better positive predictive value as clinicians. Towards more general and reliable model more data is needed and collection of training data should be systematic.

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Citation Download Citation

Ilkka Pölönen, Samuli Rahkonen, Leevi Annala, and Noora Neittaanmäki "Convolutional neural networks in skin cancer detection using spatial and spectral domain", Proc. SPIE 10851, Photonics in Dermatology and Plastic Surgery 2019, 108510B (26 February 2019); https://doi.org/10.1117/12.2509871

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