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Feature-Based vs. Deep-Learning Fusion Methods for the In Vivo Detection of Radiation Dermatitis Using Optical Coherence Tomography, a Feasibility Study

Crossref DOI link: https://doi.org/10.1007/s10278-024-01241-4

Published Online: 2024-09-04

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Photiou, Christos https://orcid.org/0000-0002-5843-4288
Cloconi, Constantina https://orcid.org/0000-0002-9126-8082
Strouthos, Iosif https://orcid.org/0000-0001-6229-5471
Funding

Funding for this research was provided by:

European Commission (739551)

University of Cyprus
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Text and Data Mining valid from 2024-09-04

Version of Record valid from 2024-09-04
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Article History

Received: 23 May 2024

Revised: 7 August 2024

Accepted: 18 August 2024

First Online: 4 September 2024

Declarations

:

: This study was performed in accordance with the legislation of the Republic of Cyprus. Approval was granted by the Bioethics Committee of Cyprus (Jan 11 2021 / No: ΕΕΒΚ/ΕΠ/2020/61).

: Informed consent was obtained from all individual participants included in the study. The authors affirm that human research participants provided informed consent for publication of the image in Fig. A,

: The authors have no relevant financial interests in this article and no potential conflicts of interest to disclose.

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