Phase quantized polar transformative with cellular automaton for early glaucoma detection

Glaucoma is the leading cause of blindness worldwide. Glaucoma being a chronic eye disease results in irreversible loss of vision. Everyone is at danger for glaucoma. But, certain groups are greater risk. Hence, accurate Classification of normal and glaucoma images is significant one. In the screeni...

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Autores principales:	Narmatha Venugopal, Kamarasan Mari, G. Manikandan, K.R. Sekar
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Optimal coherence tomography First order Phase quantization Differential polar transformation Cellular automaton Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/eee0980ad46a44ddbd4d6e55378c161b
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spelling	oai:doaj.org-article:eee0980ad46a44ddbd4d6e55378c161b2021-11-22T04:22:29ZPhase quantized polar transformative with cellular automaton for early glaucoma detection2090-447910.1016/j.asej.2021.04.018https://doaj.org/article/eee0980ad46a44ddbd4d6e55378c161b2021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2090447921002021https://doaj.org/toc/2090-4479Glaucoma is the leading cause of blindness worldwide. Glaucoma being a chronic eye disease results in irreversible loss of vision. Everyone is at danger for glaucoma. But, certain groups are greater risk. Hence, accurate Classification of normal and glaucoma images is significant one. In the screening and early detection of glaucoma, Cup to Disc Ratio (CDR) method plays a significant role. The automatic segmentation for early detection from Optimal Coherence Tomography (OCT) images is a fundamental task. Several research works based on OCT were contributed for early detection of glacuoma. However, inherent feature extraction and over fitting issues while performing early glaucoma detection have been researched by the research community for long time. In this paper, we propose Artificial Intelligence architecture, called Phase Quantized Polar Transformed Cellular Automaton (PQPT-CA) method that use the displacement gradients and distance gradients for early glaucoma detection. The proposed PQPT-CA method comprises of inherent feature extraction, robust feature segmentation and early glaucoma detection based on OCT. To start with, First Order Phase Quantization model is applied to the raw input image for extracting inherent features. Next, with the extracted features, Differential Polar Transformation is applied to generate robust segmentation map. Finally, glaucoma detection is performed for three different state employing Cellular Automaton model. The experiments show that our PQPT-CA method achieves state-of-the-art early detection on ACRIMA database. Simultaneously, the proposed method also obtains the satisfactory glaucoma screening performances with calculated diagnosis accuracy on ACRIMA database. The PQPT-CA method increases the Diagnosis Accuracy by 24% and minimizes computational time and false positive rate by 21% and 54% respectively.Narmatha VenugopalKamarasan MariG. ManikandanK.R. SekarElsevierarticleOptimal coherence tomographyFirst orderPhase quantizationDifferential polar transformationCellular automatonEngineering (General). Civil engineering (General)TA1-2040ENAin Shams Engineering Journal, Vol 12, Iss 4, Pp 4145-4155 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Optimal coherence tomography First order Phase quantization Differential polar transformation Cellular automaton Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	Optimal coherence tomography First order Phase quantization Differential polar transformation Cellular automaton Engineering (General). Civil engineering (General) TA1-2040 Narmatha Venugopal Kamarasan Mari G. Manikandan K.R. Sekar Phase quantized polar transformative with cellular automaton for early glaucoma detection
description	Glaucoma is the leading cause of blindness worldwide. Glaucoma being a chronic eye disease results in irreversible loss of vision. Everyone is at danger for glaucoma. But, certain groups are greater risk. Hence, accurate Classification of normal and glaucoma images is significant one. In the screening and early detection of glaucoma, Cup to Disc Ratio (CDR) method plays a significant role. The automatic segmentation for early detection from Optimal Coherence Tomography (OCT) images is a fundamental task. Several research works based on OCT were contributed for early detection of glacuoma. However, inherent feature extraction and over fitting issues while performing early glaucoma detection have been researched by the research community for long time. In this paper, we propose Artificial Intelligence architecture, called Phase Quantized Polar Transformed Cellular Automaton (PQPT-CA) method that use the displacement gradients and distance gradients for early glaucoma detection. The proposed PQPT-CA method comprises of inherent feature extraction, robust feature segmentation and early glaucoma detection based on OCT. To start with, First Order Phase Quantization model is applied to the raw input image for extracting inherent features. Next, with the extracted features, Differential Polar Transformation is applied to generate robust segmentation map. Finally, glaucoma detection is performed for three different state employing Cellular Automaton model. The experiments show that our PQPT-CA method achieves state-of-the-art early detection on ACRIMA database. Simultaneously, the proposed method also obtains the satisfactory glaucoma screening performances with calculated diagnosis accuracy on ACRIMA database. The PQPT-CA method increases the Diagnosis Accuracy by 24% and minimizes computational time and false positive rate by 21% and 54% respectively.
format	article
author	Narmatha Venugopal Kamarasan Mari G. Manikandan K.R. Sekar
author_facet	Narmatha Venugopal Kamarasan Mari G. Manikandan K.R. Sekar
author_sort	Narmatha Venugopal
title	Phase quantized polar transformative with cellular automaton for early glaucoma detection
title_short	Phase quantized polar transformative with cellular automaton for early glaucoma detection
title_full	Phase quantized polar transformative with cellular automaton for early glaucoma detection
title_fullStr	Phase quantized polar transformative with cellular automaton for early glaucoma detection
title_full_unstemmed	Phase quantized polar transformative with cellular automaton for early glaucoma detection
title_sort	phase quantized polar transformative with cellular automaton for early glaucoma detection
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/eee0980ad46a44ddbd4d6e55378c161b
work_keys_str_mv	AT narmathavenugopal phasequantizedpolartransformativewithcellularautomatonforearlyglaucomadetection AT kamarasanmari phasequantizedpolartransformativewithcellularautomatonforearlyglaucomadetection AT gmanikandan phasequantizedpolartransformativewithcellularautomatonforearlyglaucomadetection AT krsekar phasequantizedpolartransformativewithcellularautomatonforearlyglaucomadetection
_version_	1718418255631089664

Phase quantized polar transformative with cellular automaton for early glaucoma detection

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