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A Generic Pixel Pitch Calibration Method for Fundus Camera via Automated ROI Extraction

Pixel pitch calibration is an essential step to make the fundus structures in the fundus image quantitatively measurable, which is important for the diagnosis and treatment of many diseases, e.g., diabetes, arteriosclerosis, hereditary optic atrophy, etc. The conventional calibration approaches requ...

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Autores principales: Long, Tengfei, Xu, Yi, Zou, Haidong, Lu, Lina, Yuan, Tianyi, Dong, Zhou, Dong, Jiqun, Ke, Xin, Ling, Saiguang, Ma, Yingyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9653591/
https://www.ncbi.nlm.nih.gov/pubmed/36366262
http://dx.doi.org/10.3390/s22218565
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author Long, Tengfei
Xu, Yi
Zou, Haidong
Lu, Lina
Yuan, Tianyi
Dong, Zhou
Dong, Jiqun
Ke, Xin
Ling, Saiguang
Ma, Yingyan
author_facet Long, Tengfei
Xu, Yi
Zou, Haidong
Lu, Lina
Yuan, Tianyi
Dong, Zhou
Dong, Jiqun
Ke, Xin
Ling, Saiguang
Ma, Yingyan
author_sort Long, Tengfei
collection PubMed
description Pixel pitch calibration is an essential step to make the fundus structures in the fundus image quantitatively measurable, which is important for the diagnosis and treatment of many diseases, e.g., diabetes, arteriosclerosis, hereditary optic atrophy, etc. The conventional calibration approaches require the specific parameters of the fundus camera or several specially shot images of the chess board, but these are generally not accessible, and the calibration results cannot be generalized to other cameras. Based on automated ROI (region of interest) and optic disc detection, the diameter ratio of ROI and optic disc (ROI–disc ratio) is quantitatively analyzed for a large number of fundus images. With the prior knowledge of the average diameter of an optic disc in fundus, the pixel pitch can be statistically estimated from a large number of fundus images captured by a specific camera without the availability of chess board images or detailed specifics of the fundus camera. Furthermore, for fundus cameras of FOV (fixed field-of-view), the pixel pitch of a fundus image of 45° FOV can be directly estimated according to the automatically measured diameter of ROI in the pixel. The average ROI–disc ratio is approximately constant, i.e., 6.404 ± 0.619 in the pixel, according to 40,600 fundus images, captured by different cameras, of 45° FOV. In consequence, the pixel pitch of a fundus image of 45° FOV can be directly estimated according to the automatically measured diameter of ROI in the pixel, and results show the pixel pitches of Canon CR2, Topcon NW400, Zeiss Visucam 200, and Newvision RetiCam 3100 cameras are 6.825 ± 0.666 μm, 6.625 ± 0.647 μm, 5.793 ± 0.565 μm, and 5.884 ± 0.574 μm, respectively. Compared with the manually measured pixel pitches, based on the method of ISO 10940:2009, i.e., 6.897 μm, 6.807 μm, 5.693 μm, and 6.050 μm, respectively, the bias of the proposed method is less than 5%. Since our method doesn’t require chess board images or detailed specifics, the fundus structures on the fundus image can be measured accurately, according to the pixel pitch obtained by this method, without knowing the type and parameters of the camera.
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spelling pubmed-96535912022-11-15 A Generic Pixel Pitch Calibration Method for Fundus Camera via Automated ROI Extraction Long, Tengfei Xu, Yi Zou, Haidong Lu, Lina Yuan, Tianyi Dong, Zhou Dong, Jiqun Ke, Xin Ling, Saiguang Ma, Yingyan Sensors (Basel) Article Pixel pitch calibration is an essential step to make the fundus structures in the fundus image quantitatively measurable, which is important for the diagnosis and treatment of many diseases, e.g., diabetes, arteriosclerosis, hereditary optic atrophy, etc. The conventional calibration approaches require the specific parameters of the fundus camera or several specially shot images of the chess board, but these are generally not accessible, and the calibration results cannot be generalized to other cameras. Based on automated ROI (region of interest) and optic disc detection, the diameter ratio of ROI and optic disc (ROI–disc ratio) is quantitatively analyzed for a large number of fundus images. With the prior knowledge of the average diameter of an optic disc in fundus, the pixel pitch can be statistically estimated from a large number of fundus images captured by a specific camera without the availability of chess board images or detailed specifics of the fundus camera. Furthermore, for fundus cameras of FOV (fixed field-of-view), the pixel pitch of a fundus image of 45° FOV can be directly estimated according to the automatically measured diameter of ROI in the pixel. The average ROI–disc ratio is approximately constant, i.e., 6.404 ± 0.619 in the pixel, according to 40,600 fundus images, captured by different cameras, of 45° FOV. In consequence, the pixel pitch of a fundus image of 45° FOV can be directly estimated according to the automatically measured diameter of ROI in the pixel, and results show the pixel pitches of Canon CR2, Topcon NW400, Zeiss Visucam 200, and Newvision RetiCam 3100 cameras are 6.825 ± 0.666 μm, 6.625 ± 0.647 μm, 5.793 ± 0.565 μm, and 5.884 ± 0.574 μm, respectively. Compared with the manually measured pixel pitches, based on the method of ISO 10940:2009, i.e., 6.897 μm, 6.807 μm, 5.693 μm, and 6.050 μm, respectively, the bias of the proposed method is less than 5%. Since our method doesn’t require chess board images or detailed specifics, the fundus structures on the fundus image can be measured accurately, according to the pixel pitch obtained by this method, without knowing the type and parameters of the camera. MDPI 2022-11-07 /pmc/articles/PMC9653591/ /pubmed/36366262 http://dx.doi.org/10.3390/s22218565 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Long, Tengfei
Xu, Yi
Zou, Haidong
Lu, Lina
Yuan, Tianyi
Dong, Zhou
Dong, Jiqun
Ke, Xin
Ling, Saiguang
Ma, Yingyan
A Generic Pixel Pitch Calibration Method for Fundus Camera via Automated ROI Extraction
title A Generic Pixel Pitch Calibration Method for Fundus Camera via Automated ROI Extraction
title_full A Generic Pixel Pitch Calibration Method for Fundus Camera via Automated ROI Extraction
title_fullStr A Generic Pixel Pitch Calibration Method for Fundus Camera via Automated ROI Extraction
title_full_unstemmed A Generic Pixel Pitch Calibration Method for Fundus Camera via Automated ROI Extraction
title_short A Generic Pixel Pitch Calibration Method for Fundus Camera via Automated ROI Extraction
title_sort generic pixel pitch calibration method for fundus camera via automated roi extraction
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9653591/
https://www.ncbi.nlm.nih.gov/pubmed/36366262
http://dx.doi.org/10.3390/s22218565
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