Fully automated detection of lamina cribrosa in optical coherence tomography: Framework and illustrative examples
| Autor: | Piotr Syga, D. Robert Iskander, Cezary Sielużycki, Patrycja Krzyżanowska-Berkowska |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Optic Disk
Optic disk 02 engineering and technology Signal-To-Noise Ratio Imaging phantom Image (mathematics) 03 medical and health sciences Imaging Three-Dimensional 0302 clinical medicine Signal-to-noise ratio Optical coherence tomography 0202 electrical engineering electronic engineering information engineering Image scaling medicine Computer vision Mathematics medicine.diagnostic_test business.industry 020207 software engineering Pattern recognition 030221 ophthalmology & optometry A priori and a posteriori Artificial intelligence Tomography business Algorithms Tomography Optical Coherence |
| Zdroj: | EMBC |
| Popis: | We present an algorithm for automated detection of lamina cribrosa (LC) using optical coherence tomography scans. To the best of our knowledge, it is the first algorithm of this type, as previous attempts relied heavily on characteristic points marked a priori by a human expert and were hence semi-automated at best. First, we highlight the unwanted, yet unavoidable, influence of image rescaling necessary to provide the detection algorithm with real-world image proportions. Next, we simulate an LC phantom and test the influence of various combinations of the rescaling method and SNRs on the LC detection efficacy. Finally, we present some illustrative results from real-data analysis. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|