FAZSeg: A New Software for Quantification of the Foveal Avascular Zone

Various ocular diseases and high myopia influence the anatomical reference point Foveal Avascular Zone (FAZ) dimensions. Therefore, it is important to segment and quantify the FAZs dimensions accurately. To the best of our knowledge, there is no automated tool or algorithms available to segment the...

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Published inClinical ophthalmology (Auckland, N.Z.) Vol. 15; pp. 4817 - 4827
Main Authors Viekash, VK, Jothi Balaji, Janarthanam, Lakshminarayanan, Vasudevan
Format Journal Article
LanguageEnglish
Published New Zealand Dove Medical Press Limited 01.01.2021
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ISSN1177-5483
1177-5467
1177-5483
DOI10.2147/OPTH.S346145

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Abstract Various ocular diseases and high myopia influence the anatomical reference point Foveal Avascular Zone (FAZ) dimensions. Therefore, it is important to segment and quantify the FAZs dimensions accurately. To the best of our knowledge, there is no automated tool or algorithms available to segment the FAZ's deep retinal layer. The paper describes a new open-access software with a Graphical User Interface (GUI) and compares the results with the ground truth (manual segmentation). Ninety-three healthy normal subjects included 30 emmetropia and 63 myopic subjects without any sight-threatening retinal conditions, were included in the study. The 6mm x 6mm using the Angioplex protocol (Cirrus 5000 Carl Zeiss Meditec Inc., Dublin, CA) was used, and all the images were aligned with the centre of the fovea. Each FAZ image corresponding to dimensions 420×420 pixels were used in this study. These FAZ image dimensions for the superficial and deep layers were quantified using the New Automated Software Method (NAM). The NAM-based FAZ dimensions were validated with the ground truth. The age distribution for all 93 subjects was 28.02 ± 10.79 (range, 10.0-66.0) years. For normal subjects mean ± SD age distribution was 32.13 ± 16.27 years. Similarly, the myopia age distribution was 26.06 ± 6.06 years. The NAM had an accuracy of 91.40%. Moreover, the NAM on superficial layer FAZ gave a Dice Similarity Coefficient (DSC) score of 0.94 and Structural Similarity Index Metric (SSIM) of 0.97, while the NAM on deep layer FAZ gave a DSC score of 0.96 and SSIM of 0.98. A clinician-based GUI software was designed and tested on the FAZ images from deep and superficial layers. The NAM outperformed the device's inbuilt algorithm when measuring the superficial layer. This open-source software package is in the public domain and can be downloaded online.
AbstractList VK Viekash,1 Janarthanam Jothi Balaji,2 Vasudevan Lakshminarayanan3 1Department of Instrumentation and Control Engineering, National Institute of Technology, Tiruchirappalli, Tamil Nadu, 620015, India; 2Department of Optometry, Medical Research Foundation, Chennai, Tamil Nadu, 600 006, India; 3Theoretical and Experimental Epistemology Lab, School of Optometry and Vision Science, University of Waterloo, Waterloo, ON, N2L 3G1, CanadaCorrespondence: Janarthanam Jothi Balaji Tel +91 44-42271500Email jothibalaji@gmail.comIntroduction: Various ocular diseases and high myopia influence the anatomical reference point Foveal Avascular Zone (FAZ) dimensions. Therefore, it is important to segment and quantify the FAZs dimensions accurately. To the best of our knowledge, there is no automated tool or algorithms available to segment the FAZ’s deep retinal layer. The paper describes a new open-access software with a Graphical User Interface (GUI) and compares the results with the ground truth (manual segmentation).Methods: Ninety-three healthy normal subjects included 30 emmetropia and 63 myopic subjects without any sight-threatening retinal conditions, were included in the study. The 6mm x 6mm using the Angioplex protocol (Cirrus 5000 Carl Zeiss Meditec Inc., Dublin, CA) was used, and all the images were aligned with the centre of the fovea. Each FAZ image corresponding to dimensions 420× 420 pixels were used in this study. These FAZ image dimensions for the superficial and deep layers were quantified using the New Automated Software Method (NAM). The NAM-based FAZ dimensions were validated with the ground truth.Results: The age distribution for all 93 subjects was 28.02 ± 10.79 (range, 10.0– 66.0) years. For normal subjects mean ± SD age distribution was 32.13 ± 16.27 years. Similarly, the myopia age distribution was 26.06 ± 6.06 years. The NAM had an accuracy of 91.40%. Moreover, the NAM on superficial layer FAZ gave a Dice Similarity Coefficient (DSC) score of 0.94 and Structural Similarity Index Metric (SSIM) of 0.97, while the NAM on deep layer FAZ gave a DSC score of 0.96 and SSIM of 0.98.Conclusion: A clinician-based GUI software was designed and tested on the FAZ images from deep and superficial layers. The NAM outperformed the device’s inbuilt algorithm when measuring the superficial layer. This open-source software package is in the public domain and can be downloaded online.Keywords: image processing, foveal avascular zone, optical coherence tomography angiography, superficial retinal layer, deep retinal layer
Introduction: Various ocular diseases and high myopia influence the anatomical reference point Foveal Avascular Zone (FAZ) dimensions. Therefore, it is important to segment and quantify the FAZs dimensions accurately. To the best of our knowledge, there is no automated tool or algorithms available to segment the FAZ's deep retinal layer. The paper describes a new open-access software with a Graphical User Interface (GUI) and compares the results with the ground truth (manual segmentation). Methods: Ninety-three healthy normal subjects included 30 emmetropia and 63 myopic subjects without any sight-threatening retinal conditions, were included in the study. The 6 mm x 6 mm using the Angioplex protocol (Cirrus 5000 Carl Zeiss Meditec Inc., Dublin, CA) was used, and all the images were aligned with the centre of the fovea. Each FAZ image corresponding to dimensions 420x420 pixels were used in this study. These FAZ image dimensions for the superficial and deep layers were quantified using the New Automated Software Method (NAM). The NAM-based FAZ dimensions were validated with the ground truth. Results: The age distribution for all 93 subjects was 28.02 [+ or -] 10.79 (range, 10.0-66.0) years. For normal subjects mean [+ or -] SD age distribution was 32.13 [+ or -] 16.27 years. Similarly, the myopia age distribution was 26.06 [+ or -] 6.06 years. The NAM had an accuracy of 91.40%. Moreover, the NAM on superficial layer FAZ gave a Dice Similarity Coefficient (DSC) score of 0.94 and Structural Similarity Index Metric (SSIM) of 0.97, while the NAM on deep layer FAZ gave a DSC score of 0.96 and SSIM of 0.98. Conclusion: A clinician-based GUI software was designed and tested on the FAZ images from deep and superficial layers. The NAM outperformed the device's inbuilt algorithm when measuring the superficial layer. This open-source software package is in the public domain and can be downloaded online. Keywords: image processing, foveal avascular zone, optical coherence tomography angiography, superficial retinal layer, deep retinal layer
Introduction: Various ocular diseases and high myopia influence the anatomical reference point Foveal Avascular Zone (FAZ) dimensions. Therefore, it is important to segment and quantify the FAZs dimensions accurately. To the best of our knowledge, there is no automated tool or algorithms available to segment the FAZ’s deep retinal layer. The paper describes a new open-access software with a Graphical User Interface (GUI) and compares the results with the ground truth (manual segmentation). Methods: Ninety-three healthy normal subjects included 30 emmetropia and 63 myopic subjects without any sight-threatening retinal conditions, were included in the study. The 6mm x 6mm using the Angioplex protocol (Cirrus 5000 Carl Zeiss Meditec Inc., Dublin, CA) was used, and all the images were aligned with the centre of the fovea. Each FAZ image corresponding to dimensions 420× 420 pixels were used in this study. These FAZ image dimensions for the superficial and deep layers were quantified using the New Automated Software Method (NAM). The NAM-based FAZ dimensions were validated with the ground truth. Results: The age distribution for all 93 subjects was 28.02 ± 10.79 (range, 10.0– 66.0) years. For normal subjects mean ± SD age distribution was 32.13 ± 16.27 years. Similarly, the myopia age distribution was 26.06 ± 6.06 years. The NAM had an accuracy of 91.40%. Moreover, the NAM on superficial layer FAZ gave a Dice Similarity Coefficient (DSC) score of 0.94 and Structural Similarity Index Metric (SSIM) of 0.97, while the NAM on deep layer FAZ gave a DSC score of 0.96 and SSIM of 0.98. Conclusion: A clinician-based GUI software was designed and tested on the FAZ images from deep and superficial layers. The NAM outperformed the device’s inbuilt algorithm when measuring the superficial layer. This open-source software package is in the public domain and can be downloaded online.
Various ocular diseases and high myopia influence the anatomical reference point Foveal Avascular Zone (FAZ) dimensions. Therefore, it is important to segment and quantify the FAZs dimensions accurately. To the best of our knowledge, there is no automated tool or algorithms available to segment the FAZ's deep retinal layer. The paper describes a new open-access software with a Graphical User Interface (GUI) and compares the results with the ground truth (manual segmentation).INTRODUCTIONVarious ocular diseases and high myopia influence the anatomical reference point Foveal Avascular Zone (FAZ) dimensions. Therefore, it is important to segment and quantify the FAZs dimensions accurately. To the best of our knowledge, there is no automated tool or algorithms available to segment the FAZ's deep retinal layer. The paper describes a new open-access software with a Graphical User Interface (GUI) and compares the results with the ground truth (manual segmentation).Ninety-three healthy normal subjects included 30 emmetropia and 63 myopic subjects without any sight-threatening retinal conditions, were included in the study. The 6mm x 6mm using the Angioplex protocol (Cirrus 5000 Carl Zeiss Meditec Inc., Dublin, CA) was used, and all the images were aligned with the centre of the fovea. Each FAZ image corresponding to dimensions 420×420 pixels were used in this study. These FAZ image dimensions for the superficial and deep layers were quantified using the New Automated Software Method (NAM). The NAM-based FAZ dimensions were validated with the ground truth.METHODSNinety-three healthy normal subjects included 30 emmetropia and 63 myopic subjects without any sight-threatening retinal conditions, were included in the study. The 6mm x 6mm using the Angioplex protocol (Cirrus 5000 Carl Zeiss Meditec Inc., Dublin, CA) was used, and all the images were aligned with the centre of the fovea. Each FAZ image corresponding to dimensions 420×420 pixels were used in this study. These FAZ image dimensions for the superficial and deep layers were quantified using the New Automated Software Method (NAM). The NAM-based FAZ dimensions were validated with the ground truth.The age distribution for all 93 subjects was 28.02 ± 10.79 (range, 10.0-66.0) years. For normal subjects mean ± SD age distribution was 32.13 ± 16.27 years. Similarly, the myopia age distribution was 26.06 ± 6.06 years. The NAM had an accuracy of 91.40%. Moreover, the NAM on superficial layer FAZ gave a Dice Similarity Coefficient (DSC) score of 0.94 and Structural Similarity Index Metric (SSIM) of 0.97, while the NAM on deep layer FAZ gave a DSC score of 0.96 and SSIM of 0.98.RESULTSThe age distribution for all 93 subjects was 28.02 ± 10.79 (range, 10.0-66.0) years. For normal subjects mean ± SD age distribution was 32.13 ± 16.27 years. Similarly, the myopia age distribution was 26.06 ± 6.06 years. The NAM had an accuracy of 91.40%. Moreover, the NAM on superficial layer FAZ gave a Dice Similarity Coefficient (DSC) score of 0.94 and Structural Similarity Index Metric (SSIM) of 0.97, while the NAM on deep layer FAZ gave a DSC score of 0.96 and SSIM of 0.98.A clinician-based GUI software was designed and tested on the FAZ images from deep and superficial layers. The NAM outperformed the device's inbuilt algorithm when measuring the superficial layer. This open-source software package is in the public domain and can be downloaded online.CONCLUSIONA clinician-based GUI software was designed and tested on the FAZ images from deep and superficial layers. The NAM outperformed the device's inbuilt algorithm when measuring the superficial layer. This open-source software package is in the public domain and can be downloaded online.
Various ocular diseases and high myopia influence the anatomical reference point Foveal Avascular Zone (FAZ) dimensions. Therefore, it is important to segment and quantify the FAZs dimensions accurately. To the best of our knowledge, there is no automated tool or algorithms available to segment the FAZ's deep retinal layer. The paper describes a new open-access software with a Graphical User Interface (GUI) and compares the results with the ground truth (manual segmentation). Ninety-three healthy normal subjects included 30 emmetropia and 63 myopic subjects without any sight-threatening retinal conditions, were included in the study. The 6mm x 6mm using the Angioplex protocol (Cirrus 5000 Carl Zeiss Meditec Inc., Dublin, CA) was used, and all the images were aligned with the centre of the fovea. Each FAZ image corresponding to dimensions 420×420 pixels were used in this study. These FAZ image dimensions for the superficial and deep layers were quantified using the New Automated Software Method (NAM). The NAM-based FAZ dimensions were validated with the ground truth. The age distribution for all 93 subjects was 28.02 ± 10.79 (range, 10.0-66.0) years. For normal subjects mean ± SD age distribution was 32.13 ± 16.27 years. Similarly, the myopia age distribution was 26.06 ± 6.06 years. The NAM had an accuracy of 91.40%. Moreover, the NAM on superficial layer FAZ gave a Dice Similarity Coefficient (DSC) score of 0.94 and Structural Similarity Index Metric (SSIM) of 0.97, while the NAM on deep layer FAZ gave a DSC score of 0.96 and SSIM of 0.98. A clinician-based GUI software was designed and tested on the FAZ images from deep and superficial layers. The NAM outperformed the device's inbuilt algorithm when measuring the superficial layer. This open-source software package is in the public domain and can be downloaded online.
Audience Academic
Author Jothi Balaji, Janarthanam
Lakshminarayanan, Vasudevan
Viekash, VK
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CitedBy_id crossref_primary_10_3390_diagnostics13101735
crossref_primary_10_4103_IJO_IJO_2212_23
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Cites_doi 10.1371/journal.pone.0184948
10.1117/12.2544817
10.1515/chilat-2016-0014
10.1177/2474126418778492
10.1117/12.2543906
10.1111/j.1475-1313.2007.00475.x
10.1038/s41433-019-0438-7
10.1167/iovs.18-25957
10.1167/iovs.11-8488
10.1167/tvst.6.3.16
10.1097/IIO.0000000000000249
10.1117/12.2610713
10.1371/journal.pone.0219785
10.1016/j.ajo.2014.10.032
10.1038/s41433-020-0824-1
10.1001/jamaophthalmol.2019.4821
10.1097/OPX.0b013e3182504227
10.1371/journal.pone.0212364
10.1016/S0161-6420(99)00732-0
10.4103/njcp.njcp_183_16
10.1167/iovs.15-18869
10.1117/12.2594152
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Keywords image processing
deep retinal layer
foveal avascular zone
superficial retinal layer
optical coherence tomography angiography
Language English
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References ref23
Llanas (ref14) 2020; 138
Ucak (ref11) 2020; 34
Flitcroft (ref16) 2009; 60
(ref22) 2021
(ref12) 2020
Badmus (ref21) 2017; 20
Linderman (ref1) 2017; 6
Lee (ref17) 2015; 159
Jorge (ref19) 2007; 27
Dubis (ref3) 2012; 53
He (ref8) 2019; 33
Díaz (ref13) 2019; 14
Alshareef (ref7) 2018; 2
(ref15) 2020
Iyamu (ref20) 2018; 20
Chui (ref4) 2012; 89
Mehta (ref6) 2019; 59
Gołębiewska (ref9) 2019; 14
Mintz-Hittner (ref2) 1999; 106
Choi (ref5) 2017; 12
Rascevskis (ref18) 2016; 16
Tan (ref10) 2016; 57
References_xml – volume: 12
  start-page: e0184948
  year: 2017
  ident: ref5
  publication-title: PLoS One
  doi: 10.1371/journal.pone.0184948
– volume-title: Ophthalmic Technologies XXX
  year: 2020
  ident: ref12
  doi: 10.1117/12.2544817
– volume: 16
  start-page: 31
  year: 2016
  ident: ref18
  publication-title: Acta Chir Latv
  doi: 10.1515/chilat-2016-0014
– volume: 2
  start-page: 213
  year: 2018
  ident: ref7
  publication-title: J Vitreoretin Dis
  doi: 10.1177/2474126418778492
– volume-title: Ophthalmic Technologies XXX
  year: 2020
  ident: ref15
  doi: 10.1117/12.2543906
– volume: 27
  start-page: 287
  year: 2007
  ident: ref19
  publication-title: Ophthalmic Physiol Opt J
  doi: 10.1111/j.1475-1313.2007.00475.x
– volume: 33
  start-page: 1494
  year: 2019
  ident: ref8
  publication-title: Eye
  doi: 10.1038/s41433-019-0438-7
– volume: 60
  start-page: M20
  year: 2009
  ident: ref16
  publication-title: Investig Ophthalmol Vis Sci
  doi: 10.1167/iovs.18-25957
– volume: 53
  start-page: 1628
  year: 2012
  ident: ref3
  publication-title: Investig Ophthalmol Vis Sci
  doi: 10.1167/iovs.11-8488
– volume: 6
  start-page: 16
  year: 2017
  ident: ref1
  publication-title: Transl Vis Sci Technol
  doi: 10.1167/tvst.6.3.16
– volume: 59
  start-page: 241
  year: 2019
  ident: ref6
  publication-title: Int Ophthalmol Clin
  doi: 10.1097/IIO.0000000000000249
– ident: ref23
  doi: 10.1117/12.2610713
– volume: 14
  start-page: e0219785
  year: 2019
  ident: ref9
  publication-title: PLoS One
  doi: 10.1371/journal.pone.0219785
– volume: 159
  start-page: 315
  year: 2015
  ident: ref17
  publication-title: Am J Ophthalmol
  doi: 10.1016/j.ajo.2014.10.032
– volume: 20
  start-page: 77
  year: 2018
  ident: ref20
  publication-title: J Niger Optom Assoc
– volume: 34
  start-page: 1129
  year: 2020
  ident: ref11
  publication-title: Eye
  doi: 10.1038/s41433-020-0824-1
– volume: 138
  start-page: 86
  year: 2020
  ident: ref14
  publication-title: JAMA Ophthalmol
  doi: 10.1001/jamaophthalmol.2019.4821
– volume: 89
  start-page: 602
  year: 2012
  ident: ref4
  publication-title: Optom Vis Sci
  doi: 10.1097/OPX.0b013e3182504227
– volume: 14
  start-page: e0212364
  year: 2019
  ident: ref13
  publication-title: PLoS One
  doi: 10.1371/journal.pone.0212364
– volume: 106
  start-page: 1409
  year: 1999
  ident: ref2
  publication-title: Ophthalmology
  doi: 10.1016/S0161-6420(99)00732-0
– volume: 20
  start-page: 1328
  year: 2017
  ident: ref21
  publication-title: Niger J Clin Pract
  doi: 10.4103/njcp.njcp_183_16
– volume: 57
  start-page: OCT224
  year: 2016
  ident: ref10
  publication-title: Investig Ophthalmol Vis Sci
  doi: 10.1167/iovs.15-18869
– volume-title: Applications of Machine Learning 2021
  year: 2021
  ident: ref22
  doi: 10.1117/12.2594152
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Snippet Various ocular diseases and high myopia influence the anatomical reference point Foveal Avascular Zone (FAZ) dimensions. Therefore, it is important to segment...
Introduction: Various ocular diseases and high myopia influence the anatomical reference point Foveal Avascular Zone (FAZ) dimensions. Therefore, it is...
VK Viekash,1 Janarthanam Jothi Balaji,2 Vasudevan Lakshminarayanan3 1Department of Instrumentation and Control Engineering, National Institute of Technology,...
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SubjectTerms Algorithms
Automation
Biometrics
Cornea
Diabetic retinopathy
Eye diseases
foveal avascular zone
Image processing
Medical imaging
optical coherence tomography angiography
Original Research
Public software
Software
superficial retinal layer and deep retinal layer
Tomography
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Title FAZSeg: A New Software for Quantification of the Foveal Avascular Zone
URI https://www.ncbi.nlm.nih.gov/pubmed/34992342
https://www.proquest.com/docview/2620222626
https://www.proquest.com/docview/2618230787
https://pubmed.ncbi.nlm.nih.gov/PMC8714006
https://doaj.org/article/632251418b404b5aa459d054b65939e4
Volume 15
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