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Machine learning aided fiber-optical system for liver cancer diagnosis in minimally invasive surgical interventions |
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| Author: | Zherebtsov, E.1,2; Zajnulina, M.3; Kandurova, K.2; |
| Organizations: |
1University of Oulu, Optoelectronics and Measurement Techniques Unit, Oulu, Finland 2Research and Development Center of Biomedical Photonics, Orel State University, Orel, Russia 3Aston Institute of Photonic Technologies, Aston University, Birmingham, UK
4Orel Regional Clinical Hospital, 302028 Orel, Russia
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| Format: | article |
| Version: | accepted version |
| Access: | open |
| Online Access: | PDF Full Text (PDF, 2.5 MB) |
| Persistent link: | http://urn.fi/urn:nbn:fi-fe202103036410 |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers,
2020
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| Publish Date: | 2021-03-03 |
| Description: |
AbstractA flexible fibre optical probe is implemented to record the parameters of the endogenous fluorescence during minimally invasive interventions in patients with cancers of hepatoduodenal area. Using machine learning techniques, the obtained spectra are classified to indicate cancerous or healthy tissue. For this, a set of different binary classifiers has been trained and tested. The classifiers showing best performance for this task are identified. see all
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| Series: |
International conference laser optics |
| ISSN: | 2640-8201 |
| ISSN-E: | 2642-5580 |
| ISSN-L: | 2640-8201 |
| ISBN: | 978-1-7281-5233-2 |
| ISBN Print: | 978-1-7281-5232-5 |
| Pages: | 1 - 1 |
| DOI: | 10.1109/ICLO48556.2020.9285445 |
| OADOI: | https://oadoi.org/10.1109/ICLO48556.2020.9285445 |
| Host publication: |
2020 International Conference Laser Optics (ICLO) |
| Conference: |
International Conference Laser Optics |
| Type of Publication: |
A4 Article in conference proceedings |
| Field of Science: |
217 Medical engineering |
| Subjects: | |
| Funding: |
This research was funded by the Russian Science Foundation under grant number 18-15-00201 and MSCA-IF-2017 scheme (ID: 792421). |
| Copyright information: |
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