TUTCRIS - Tampereen teknillinen yliopisto

TUTCRIS

Investigating human skin using deep learning enhanced multiphoton microscopy

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
Otsikko21st International Conference on Transparent Optical Networks, ICTON 2019
KustantajaIEEE
ISBN (elektroninen)9781728127798
DOI - pysyväislinkit
TilaJulkaistu - 1 heinäkuuta 2019
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaInternational Conference on Transparent Optical Networks - Angers, Ranska
Kesto: 9 heinäkuuta 201913 heinäkuuta 2019

Julkaisusarja

NimiInternational Conference on Transparent Optical Networks
ISSN (elektroninen)2161-2064

Conference

ConferenceInternational Conference on Transparent Optical Networks
MaaRanska
KaupunkiAngers
Ajanjakso9/07/1913/07/19

Tiivistelmä

Histopathological image analysis of stained tissue slides is routinely performed by a pathologist to diagnose diseases, such as cancers. Although the approach is effective, it is labor-intensive, time-consuming and risks being biased. Therefore, it would be beneficial to develop faster and more cost-effective approaches. Multiphoton microscopy can alleviate these problems by allowing label-free imaging with high contrast. When label-free multiphoton microscopy is combined with deep learning based image analysis, a wide variety of possibilities arise for the real-time characterization and diagnosis of tissues. Here, we overview our recent work on this topic focusing on automated classification of tissue images taken from human skin near the dermoepidermal junction.