Predicting spatial displacement based on intraocular image design using convolution neural network - preliminary findings

Mohd Tamrin, Mohd Izzuddin and Che Azemin, Mohd Zulfaezal and Md Noor Rudin, Noor Fawazi and Mohd Salleh, Mohd Hazimin and Hilmi, Mohd Radzi and Alwan, Ali Amer and Shah, Asadullah (2021) Predicting spatial displacement based on intraocular image design using convolution neural network - preliminary findings. Journal of Information Systems and Digital Technologies, 3 (1). pp. 74-82. E-ISSN 2682-8790

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Abstract

The main global cause for blindness is due to cataract. The common treatment for cataract is to have the cloudy natural lens removed and replaced with an artificial intraocular lens (IOL). Success in the post cataract surgery depends on the design and quality of the IOL implanted on the eye. ISO11979-3 is the standard adhered to by many lens manufacturers, to test the mechanical stability of the lenses that they produced. This compression test experiments on the lab are very costly and time consuming. Alternatively, we propose to use the convolution neural network (CNN) to predict the spatial displacement response based on the intraocular image designs. Due to limited number of images in the datasets, data augmentation was performed to transform these images and increase the sample size to 240. On top of this, the ResNet-50 deep learning network architecture was utilized to transfer the learning done on over millions of images. The final RMSE value for the training set, validation set and testing set were at 0.47mm, 2.93mm and 2.92mm respectively. The model predictabillity is well within the range recommended by the standard between 0.15 to 1.98 mm.

Item Type:	Article (Journal)
Additional Information:	5594/89550
Uncontrolled Keywords:	Intraocular Lens (IOL), Spatial Displacement, Convolution Neural Network (CNN).
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Allied Health Sciences Kulliyyah of Allied Health Sciences > Department of Optometry and Visual Science Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Science
Depositing User:	Mohd Izzuddin Mohd Tamrin
Date Deposited:	26 Apr 2021 10:01
Last Modified:	26 Apr 2021 10:01
URI:	http://irep.iium.edu.my/id/eprint/89550

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