Using A Cropping Technique or Not: Impacts on SVM-based AMD Detection on OCT Images
This paper compares the system performance of distinct flows with automatic image cropping to without automatic image cropping for age-related macular degeneration (AMD) detection on optical coherence tomography (OCT) images. Using the image cropping, the computational time of noise removal and feat...
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| Main Authors: | , , , , , |
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| Format: | Conference or Workshop Item |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2019
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070449570&doi=10.1109%2fAICAS.2019.8771609&partnerID=40&md5=9fa13736e8774bf6e23cb3b527d65084 http://eprints.utp.edu.my/23566/ |
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| Summary: | This paper compares the system performance of distinct flows with automatic image cropping to without automatic image cropping for age-related macular degeneration (AMD) detection on optical coherence tomography (OCT) images. Using the image cropping, the computational time of noise removal and feature extraction can be significantly reduced by a small loss of detection accuracy. The simulation results show that using the image cropping at the first stage achieves 93.4 accuracy. Compared to the flow without image cropping, using the image cropping loses only 0.5 accuracy but saves about 12 hours computational time and about a half of memory storages. © 2019 IEEE. |
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