Using A Cropping Technique or Not: Impacts on SVM-based AMD Detection on OCT Images

Ko, C.-E. and Chen, P.-H. and Liao, W.-M. and Lu, C.-K. and Lin, C.-H. and Liang, J.-W. (2019) Using A Cropping Technique or Not: Impacts on SVM-based AMD Detection on OCT Images. In: UNSPECIFIED.

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Abstract

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.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Impact Factor: cited By 2
Uncontrolled Keywords: Artificial intelligence; Feature extraction; Ophthalmology; Support vector machines; Tomography, Age-related macular degeneration; Computational time; Detection accuracy; Image cropping; Memory storage; Noise removal; OCT images, Optical tomography
Depositing User: Ms Sharifah Fahimah Saiyed Yeop
Date Deposited: 19 Aug 2021 07:56
Last Modified: 19 Aug 2021 07:56
URI: http://scholars.utp.edu.my/id/eprint/23566

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