Convolutional neural networks in skin cancer detection using spatial and spectral domain
Pölönen, I., Rahkonen, S., Annala, L., & Neittaanmäki, N. (2019). Convolutional neural networks in skin cancer detection using spatial and spectral domain. In B. Choi, & H. Zeng (Eds.), Proceedings of SPIE Volume 10851 : Photonics in Dermatology and Plastic Surgery 2019 (pp. 108510B). SPIE conference proceedings, 10851. SPIE, The International Society for Optical Engineering. doi:10.1117/12.2509871
Published inSPIE conference proceedings
© Society of Photo-Optical Instrumentation Engineers (SPIE), 2019.
Skin cancers are 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.