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

Lindholm, Vivian; Raita-Hakola, Anna-Maria; Annala, Leevi; Salmivuori, Mari; Jeskanen, Leila; Koskenmies, Sari; Pitkänen, Sari; Saari, Heikki; Pölönen, Ilkka; Isoherranen, Kirsi; Ranki, Annamari

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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

Julkaistu sarjassa

Acta Dermato-Venereologica

Tekijät

Lindholm, Vivian |

Raita-Hakola, Anna-Maria |

Annala, Leevi |

Salmivuori, Mari |

Jeskanen, Leila |

Koskenmies, Sari |

Pitkänen, Sari |

Saari, Heikki |

Pölönen, Ilkka |

Isoherranen, Kirsi |

Ranki, Annamari

Päivämäärä

2022

Tekijänoikeudet

Julkaisija

Society for Publication of Acta Dermato-Venereologica

Konferenssi

Congress of Nordic Dermatology and Venereology

Kuuluu julkaisuun

Abstracts from 35th Congress of Nordic Dermatology and Venereology

ISSN Hae Julkaisufoorumista

0001-5555

Lisenssi

Ellei muuten mainita, aineiston lisenssi on CC BY-NC 4.0

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Differentiating Malignant from Benign Pigmented or Non-Pigmented Skin Tumours : A Pilot Study on 3D Hyperspectral Imaging of Complex Skin Surfaces and Convolutional Neural Networks

Lindholm, Vivian; Raita-Hakola, Anna-Maria; Annala, Leevi; Salmivuori, Mari; Jeskanen, Leila; Saari, Heikki; Koskenmies, Sari; Pitkänen, Sari; Pölönen, Ilkka; Isoherranen, Kirsi; Ranki, Annamari (MDPI AG, 2022)

Several optical imaging techniques have been developed to ease the burden of skin cancer disease on our health care system. Hyperspectral images can be used to identify biological tissues by their diffuse reflected spectra. ...
Discriminating Basal Cell Carcinoma and Bowen’s Disease with Novel Hyperspectral Imaging System and Convolutional Neural Networks

Salmivuori, Mari; Lindholm, Vivian; Annala, Leevi; Raita-Hakola, Anna-Maria; Jeskanen, Leila; Pölönen, Ilkka; Koskenmies, Sari; Pitkänen, Sari; Isoherranen, Kirsi; Ranki, Annamari (Society for Publication of Acta Dermato-Venereologica, 2022)
Discriminating basal cell carcinoma and Bowen's disease from benign skin lesions with a 3D hyperspectral imaging system and convolutional neural networks

Lindholm, Vivian; Annala, Leevi; Koskenmies, Sari; Pitkänen, Sari; Isoherranen, Kirsi; Järvinen, Anna; Jeskanen, Leila; Pölönen, Ilkka; Ranki, Annamari; Raita‐Hakola, Anna‐Maria; Salmivuori, Mari (Wiley-Blackwell, 2024)
Hyperspectral Imaging Reveals Spectral Differences and Can Distinguish Malignant Melanoma from Pigmented Basal Cell Carcinomas : A Pilot Study

Räsänen, Janne; Salmivuori, Mari; Pölönen, Ilkka; Grönroos, Mari; Neittaanmäki, Noora (Society for Publication of Acta Dermato-Venereologica, 2021)

Pigmented basal cell carcinomas can be difficult to distinguish from melanocytic tumours. Hyperspectral imaging is a non-invasive imaging technique that measures the reflectance spectra of skin in vivo. The aim of this ...
FPI Based Hyperspectral Imager for the Complex Surfaces : Calibration, Illumination and Applications

Raita-Hakola, Anna-Maria; Annala, Leevi; Lindholm, Vivian; Trops, Roberts; Näsilä, Antti; Saari, Heikki; Ranki, Annamari; Pölönen, Ilkka (MDPI AG, 2022)

Hyperspectral imaging (HSI) applications for biomedical imaging and dermatological applications have been recently under research interest. Medical HSI applications are non-invasive methods with high spatial and spectral ...