Isfahan University of Medical Sciences

Science Communicator Platform

Stay connected! Follow us on X network (Twitter):
Share this content! On (X network) By
Statistical Modeling of Retinal Optical Coherence Tomography Publisher Pubmed



Amini Z1 ; Rabbani H2
Authors
Show Affiliations
Authors Affiliations
  1. 1. Research Center, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, 81745319, Iran
  2. 2. Medical Image and Signal Processing Research Center, Isfahan University of Medical Sciences, Isfahan, 81745319, Iran

Source: IEEE Transactions on Medical Imaging Published:2016


Abstract

In this paper, a new model for retinal Optical Coherence Tomography (OCT) images is proposed. This statistical model is based on introducing a nonlinear Gaussianization transform to convert the probability distribution function (pdf) of each OCT intra-retinal layer to a Gaussian distribution. The retina is a layered structure and in OCT each of these layers has a specific pdf which is corrupted by speckle noise, therefore a mixture model for statistical modeling of OCT images is proposed. A Normal-Laplace distribution, which is a convolution of a Laplace pdf and Gaussian noise, is proposed as the distribution of each component of this model. The reason for choosing Laplace pdf is the monotonically decaying behavior of OCT intensities in each layer for healthy cases. After fitting a mixture model to the data, each component is gaussianized and all of them are combined by Averaged Maximum A Posterior (AMAP) method. To demonstrate the ability of this method, a new contrast enhancement method based on this statistical model is proposed and tested on thirteen healthy 3D OCTs taken by the Topcon 3D OCT and five 3D OCTs from Age-related Macular Degeneration (AMD) patients, taken by Zeiss Cirrus HD-OCT. Comparing the results with two contending techniques, the prominence of the proposed method is demonstrated both visually and numerically. Furthermore, to prove the efficacy of the proposed method for a more direct and specific purpose, an improvement in the segmentation of intra-retinal layers using the proposed contrast enhancement method as a preprocessing step, is demonstrated. © 1982-2012 IEEE.
Related Docs
View other Related Docs
1. Sparse Domain Gaussianization for Multi-Variate Statistical Modeling of Retinal Oct Images, IEEE Transactions on Image Processing (2020)
2. Statistical Modeling of Retinal Optical Coherence Tomography Using the Weibull Mixture Model, Biomedical Optics Express (2021)
3. Oct Image Denoising Based on Asymmetric Normal Laplace Mixture Model, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (2019)
4. Optical Coherence Tomography Image Denoising Using Gaussianization Transform, Journal of Biomedical Optics (2017)
5. Multivariate Statistical Modeling of Retinal Optical Coherence Tomography, IEEE Transactions on Medical Imaging (2020)
6. Statistical Modeling of Optical Coherence Tomography Images by Asymmetric Normal Laplace Mixture Model, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (2017)
7. Modeling of Retinal Optical Coherence Tomography Based on Stochastic Differential Equations: Application to Denoising, IEEE Transactions on Medical Imaging (2021)
8. Retinal Oct Image Denoising Based on Adaptive Bessel K-Form Modeling, 2023 30th National and 8th International Iranian Conference on Biomedical Engineering, ICBME 2023 (2023)
Experts (# of related papers)
View all Related Experts
Hossein Rabbani (73)
Raheleh Kafieh (32)
Other Related Docs
9. Optical Coherence Tomography Noise Reduction Using Anisotropic Local Bivariate Gaussian Mixture Prior in 3D Complex Wavelet Domain, International Journal of Biomedical Imaging (2013)
10. Super-Resolution of Retinal Optical Coherence Tomography Images Using Statistical Modeling, Journal of Medical Signals and Sensors (2024)
11. Three Dimensional Data-Driven Multi Scale Atomic Representation of Optical Coherence Tomography, IEEE Transactions on Medical Imaging (2015)
12. Local Self-Similar Solution of Admm for Denoising of Retinal Oct Images, IEEE Transactions on Instrumentation and Measurement (2024)
13. Optical Coherence Tomography Noise Reduction Over Learned Dictionaries With Introduction of Complex Wavelet for Start Dictionary, Proceedings of SPIE - The International Society for Optical Engineering (2013)
14. Wavelet-Domain Medical Image Denoising Using Bivariate Laplacian Mixture Model, IEEE Transactions on Biomedical Engineering (2009)
15. Retinal Optical Coherence Tomography Image Analysis by a Restricted Boltzmann Machine, Biomedical Optics Express (2022)
16. Automatic Diagnosis of Abnormal Macula in Retinal Optical Coherence Tomography Images Using Wavelet-Based Convolutional Neural Network Features and Random Forests Classifier, Journal of Biomedical Optics (2018)
17. Evaluation of Asymmetry in Right and Left Eyes of Normal Individuals Using Extracted Features From Optical Coherence Tomography and Fundus Images, Journal of Medical Signals and Sensors (2021)
18. A Statistical Model for 3D Segmentation of Retinal Choroid in Optical Coherence Tomography Images, Progress in Biomedical Optics and Imaging - Proceedings of SPIE (2014)
19. Wavelet-Based Convolutional Mixture of Experts Model: An Application to Automatic Diagnosis of Abnormal Macula in Retinal Optical Coherence Tomography Images, Iranian Conference on Machine Vision and Image Processing, MVIP (2017)
20. A Review of Algorithms for Segmentation of Optical Coherence Tomography From Retina, Journal of Medical Signals and Sensors (2013)
21. Intra-Retinal Layer Segmentation of 3D Optical Coherence Tomography Using Coarse Grained Diffusion Map, Medical Image Analysis (2013)
22. Macular Oct Classification Using a Multi-Scale Convolutional Neural Network Ensemble, IEEE Transactions on Medical Imaging (2018)
23. Image Denoising Employing Local Mixture Models in Sparse Domains, IET Image Processing (2010)
24. X-Let's Atom Combinations for Modeling and Denoising of Oct Images by Modified Morphological Component Analysis, IEEE Transactions on Medical Imaging (2024)
25. Curvature Correction of Retinal Octs Using Graph-Based Geometry Detection, Physics in Medicine and Biology (2013)
26. Three-Dimensional Optical Coherence Tomography Image Denoising Through Multi-Input Fully-Convolutional Networks, Computers in Biology and Medicine (2019)
27. Optical Coherence Tomography Retinal Image Reconstruction Via Nonlocal Weighted Sparse Representation, Journal of Biomedical Optics (2018)
28. Super-Resolution of Optical Coherence Tomography Images by Scale Mixture Models, IEEE Transactions on Image Processing (2020)
29. Mathematical Analysis of Texture Indicators for the Segmentation of Optical Coherence Tomography Images, Optik (2020)
30. Three-Dimensional Curvelet-Based Dictionary Learning for Speckle Noise Removal of Optical Coherence Tomography, Biomedical Optics Express (2020)
31. Analysis of a Novel Segmentation Algorithm for Optical Coherence Tomography Images Based on Pixels Intensity Correlations, IEEE Transactions on Instrumentation and Measurement (2021)
32. Stochastic Differential Equations for Automatic Quality Control of Retinal Optical Coherence Tomography Images, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (2022)
33. Local Comparison of Cup to Disc Ratio in Right and Left Eyes Based on Fusion of Color Fundus Images and Oct B-Scans, Information Fusion (2019)
34. Bandlets on Oriented Graphs: Application to Medical Image Enhancement, IEEE Access (2019)
35. Tensor Ring Decomposition Guided Dictionary Learning for Oct Image Denoising, IEEE Transactions on Medical Imaging (2024)
36. Video Denoising in Three-Dimensional Complex Wavelet Domain Using a Doubly Stochastic Modelling, IET Image Processing (2012)
37. Speckle Noise Reduction of Medical Ultrasound Images in Complex Wavelet Domain Using Mixture Priors, IEEE Transactions on Biomedical Engineering (2008)
38. Mixture of Symmetric Stable Distributions for Macular Pathology Detection in Optical Coherence Tomography Scans, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (2022)
39. Letter to the Editor: Correction to “The Normal-Laplace Distribution and Its Relatives”, Communications in Statistics - Theory and Methods (2017)
40. Forming Optimal Projection Images From Intra-Retinal Layers Using Curvelet-Based Image Fusion Method, Journal of Medical Signals and Sensors (2020)
41. Thickness Mapping of Eleven Retinal Layers Segmented Using the Diffusion Maps Method in Normal Eyes, Journal of Ophthalmology (2015)
42. 3D Curvelet-Based Segmentation & Quantification of Drusen in Optical Coherence Tomography Images, Journal of Electrical and Computer Engineering (2017)
43. Morphological Component Analysis for Automatic Segmentation of Six Lower Retina Layers in Optical Coherence Tomography Images, Journal of Isfahan Medical School (2016)
44. A Device-Independent, Shape Preserving Retinal Optical Coherence Tomography Image Alignment Method Applying Tv-Unet for Rpe Layer Detection, IEEE Transactions on Instrumentation and Measurement (2022)
45. Isfahan Misp Dataset, Journal of Medical Signals and Sensors (2017)
46. A Matlab Package for Automatic Extraction of Flow Index in Oct-A Images by Intelligent Vessel Manipulation, SoftwareX (2020)
47. An Automatic Algorithm for Segmentation of the Boundaries of Corneal Layers in Optical Coherence Tomography Images Using Gaussian Mixture Model, Journal of Medical Signals and Sensors (2014)
48. Automatic Detection of Microaneurysms in Oct Images Using Bag of Features, Computational and Mathematical Methods in Medicine (2022)
49. Evaluation of Asymmetricity of Retinal Nerve Fiber Layer and Total Retina in Right and Left Eyes of Normal Subjects Using Extracted Features From Optical Coherence Tomography, Journal of Isfahan Medical School (2013)
50. Obtaining Thickness Maps of Corneal Layers Using the Optimal Algorithm for Intracorneal Layer Segmentation, International Journal of Biomedical Imaging (2016)