CNN-based demosaicing for labeled fluorescence cancer intraoperative imaging with visible-NIR sensors
Single-chip imaging devices with vertically stacked photodiodes and pixelated spectral filters enhance multi-dye imaging techniques for cancer surgeries. However, this advancement sacrifices spatial resolution. To address this issue, we have created a deep convolutional neural network designed to demosaic color and NIR channels, and its effectiveness has been confirmed through testing on both preclinical and clinical datasets.
Authors
- Shuming Nie (ORCID: https://orcid.org/0000-0002-7328-1144)
- Viktor Gruev (ORCID: https://orcid.org/0000-0003-1280-7971)
- Борислав Кондов (ORCID: https://orcid.org/0000-0002-7487-2552)
- Горан Кондов (ORCID: https://orcid.org/0000-0003-4567-4263)
- Yifei Jin (ORCID: https://orcid.org/0000-0002-3061-6709)
- Sunil Kumar Singhal (ORCID: https://orcid.org/0000-0002-2413-7082)
Institutions
- University of Illinois System (US)
- Ss. Cyril and Methodius University in Skopje (MK)
Publication Details
- Published
- 2025-03-20
- DOI
- https://doi.org/10.1117/12.3044342
- Primary Topic
- Nanoplatforms for cancer theranostics
- Type
- article
- Field-Weighted Citation Impact
- 0.00