6533b86ffe1ef96bd12ce73c
RESEARCH PRODUCT
Convolutional neural networks in skin cancer detection using spatial and spectral domain
Samuli RahkonenNoora NeittaanmäkiIlkka PölönenLeevi Annalasubject
ta113Training setskin cancerArtificial neural networkComputer sciencebusiness.industryspektrikuvausHyperspectral imagingspectral imagingSpectral domainPattern recognitionneuroverkotmedicine.diseaseneural networksWorld wideConvolutional neural networkihosyöpämedicineArtificial intelligenceSkin cancerEarly phasebusinessta217description
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. peerReviewed
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2019-02-26 |