Automated Monitoring for Optical Coherence Tomography-based Biosensing Using Deep Learning
| Autor: | Chun-Nam Yu, Heejong Kim, William Sean Kennedy, Shreyas Shah, Michael S. Eggleston |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
020205 medical informatics
medicine.diagnostic_test Computer science business.industry Pipeline (computing) Deep learning 02 engineering and technology Convolutional neural network Optical coherence tomography 0202 electrical engineering electronic engineering information engineering medicine Computer vision Artificial intelligence business Biosensor |
| Zdroj: | 2020 IEEE Photonics Conference (IPC). |
| DOI: | 10.1109/ipc47351.2020.9252523 |
| Popis: | Microparticle biosensors embedded in 3D tissue-mimics were spatiotemporally monitored in a completely automated pipeline using deep learning. Localization and estimation of microparticle response from OCT imaging was achieved using 3D convolutional neural networks. The automated pipeline was demonstrated using glucose-responsive microparticles as a proof-of-concept. Keywords: Optical coherence tomography, convolutional neural networks, biosensors, microparticles |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|