Leveraging 3D convolutional neural network and 3D visible-near-infrared multimodal imaging for enhanced contactless oximetry
The proposed approach offers a promising alternative for non-contact oxygen saturation measurement with good sensitivity to desaturation, showing potential for applications in clinical settings.
Authors
- Gunther Notni (ORCID: https://orcid.org/0000-0001-7532-1560)
- Alina Wildenauer (ORCID: https://orcid.org/0000-0001-5214-3431)
- Christoph Schöbel (ORCID: https://orcid.org/0000-0002-0443-2973)
- Sivagurunathan Sutharsan (ORCID: https://orcid.org/0000-0003-4069-4900)
- Karsten Seidl (ORCID: https://orcid.org/0000-0001-6197-5037)
- Belmin Alić (ORCID: https://orcid.org/0000-0002-2630-3945)
- Sarah Dietz-Terjung (ORCID: https://orcid.org/0000-0001-7907-6670)
- Chen Zhang (ORCID: https://orcid.org/0000-0001-8942-4624)
- Wang Liao (ORCID: https://orcid.org/0000-0002-1165-5171)
- Jose Guillermo Ortiz Sucre
Institutions
- Technische Universität Ilmenau (DE)
- Ruhrlandklinik (DE)
- Fraunhofer Institute for Applied Optics and Precision Engineering (DE)
- University of Duisburg-Essen (DE)
Publication Details
- Journal
- Journal of Biomedical Optics
- Published
- 2024-08-21
- DOI
- https://doi.org/10.1117/1.jbo.29.s3.s33309
- Citations
- 7
- Primary Topic
- Non-Invasive Vital Sign Monitoring
- Type
- article
- Field-Weighted Citation Impact
- 1.29