Early Pancreatic Cancer Detection Using Deep Learning and Optical Neural Networks on Integrated Photonic Chips
Employing Integrated Photonic Chip-Based Optical Neural Networks (ONNs) for early pancreatic cancer detection, achieved an average Dice score of 0.58 for 2D and 0.6412 for 3D segmentation, matching or surpassing electronic models, demonstrating ONNs as efficient, high-speed alternatives to traditional electrical training systems.
Authors
- Chun-Ju Yang
- David Z. Pan (ORCID: https://orcid.org/0000-0002-5705-2501)
- Ray T. Chen (ORCID: https://orcid.org/0000-0002-9181-4266)
- Hanqing Zhu (ORCID: https://orcid.org/0000-0003-1974-5128)
- Chenghao Feng (ORCID: https://orcid.org/0000-0002-0751-7681)
- Shupeng Ning (ORCID: https://orcid.org/0000-0002-5780-9711)
- Jiaqi Gu (ORCID: https://orcid.org/0000-0001-8535-7698)
Publication Details
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1364/cleo_at.2025.aa110_5
- Primary Topic
- Neural Networks and Reservoir Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00