Investigating human skin using deep learning enhanced multiphoton microscopy

Mikko J. Huttunen, Radu Hristu, Adrian Dumitru, Mariana Costache, Stefan G. Stanciu

Tutkimustuotos: KonferenssiartikkeliScientificvertaisarvioitu

Abstrakti

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.

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

Julkaisusarja

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

Conference

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

Julkaisufoorumi-taso

  • Jufo-taso 1

!!ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials

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