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 Optical Coherence Tomography Images by Asymmetric Normal Laplace Mixture Model Publisher Pubmed



Jorjandi S1 ; Rabbani H2 ; Kafieh R2 ; Amini Z2
Authors
Show Affiliations
Authors Affiliations
  1. 1. Student Research Center, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
  2. 2. School of Advanced Technologies in Medicine, Medical Images and Signal Processing Research Center, Isfahan University of Medical Sciences, Isfahan, Iran

Source: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS Published:2017


Abstract

Optical Coherence Tomography (OCT) is known as a non-invasive and high resolution imaging modality in ophthalmology. Effecting noise on the OCT images as well as other reasons cause a random behavior in these images. In this study, we introduce a new statistical model for retinal layers in healthy OCT images. This model, namely asymmetric Normal Laplace (NL), fits well the advent of asymmetry and heavy-tailed in intensity distribution of each layer. Due to the layered structure of retina, a mixture model is addressed. It is proposed to evaluate the fitness criteria called Kull-back Leibler Divergence (KLD) and chi-square test along visual results. The results express the well performance of proposed model in fitness of data except for 6th and 7th layers. Using a complicated model, e.g. a mixture model with two component, seems to be appropriate for these layers. The mentioned process for train images can then be devised for a test image by employing the Expectation Maximization (EM) algorithm to estimate the values of parameters in mixture model. © 2017 IEEE.
Related Docs
View other Related Docs
1. Statistical Modeling of Retinal Optical Coherence Tomography, IEEE Transactions on Medical Imaging (2016)
2. Multivariate Statistical Modeling of Retinal Optical Coherence Tomography, IEEE Transactions on Medical Imaging (2020)
3. Statistical Modeling of Retinal Optical Coherence Tomography Using the Weibull Mixture Model, Biomedical Optics Express (2021)
4. 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)
5. 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)
6. Modeling of Retinal Optical Coherence Tomography Based on Stochastic Differential Equations: Application to Denoising, IEEE Transactions on Medical Imaging (2021)
7. Sparse Domain Gaussianization for Multi-Variate Statistical Modeling of Retinal Oct Images, IEEE Transactions on Image Processing (2020)
8. A Statistical Model for 3D Segmentation of Retinal Choroid in Optical Coherence Tomography Images, Progress in Biomedical Optics and Imaging - Proceedings of SPIE (2014)
Experts (# of related papers)
View all Related Experts
Hossein Rabbani (51)
Raheleh Kafieh (22)
Other Related Docs
9. 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)
10. Mathematical Analysis of Texture Indicators for the Segmentation of Optical Coherence Tomography Images, Optik (2020)
11. Optical Coherence Tomography Noise Reduction Using Anisotropic Local Bivariate Gaussian Mixture Prior in 3D Complex Wavelet Domain, International Journal of Biomedical Imaging (2013)
12. 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)
13. Macular Oct Classification Using a Multi-Scale Convolutional Neural Network Ensemble, IEEE Transactions on Medical Imaging (2018)
14. Optical Coherence Tomography Image Denoising Using Gaussianization Transform, Journal of Biomedical Optics (2017)
15. Local Self-Similar Solution of Admm for Denoising of Retinal Oct Images, IEEE Transactions on Instrumentation and Measurement (2024)
16. Super-Resolution of Retinal Optical Coherence Tomography Images Using Statistical Modeling, Journal of Medical Signals and Sensors (2024)
17. Three Dimensional Data-Driven Multi Scale Atomic Representation of Optical Coherence Tomography, IEEE Transactions on Medical Imaging (2015)
18. Bandlets on Oriented Graphs: Application to Medical Image Enhancement, IEEE Access (2019)
19. Tensor Ring Decomposition Guided Dictionary Learning for Oct Image Denoising, IEEE Transactions on Medical Imaging (2024)
20. Retinal Optical Coherence Tomography Image Analysis by a Restricted Boltzmann Machine, Biomedical Optics Express (2022)
21. 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)
22. Super-Resolution of Optical Coherence Tomography Images by Scale Mixture Models, IEEE Transactions on Image Processing (2020)
23. Forming Projection Images From Each Layer of Retina Using Diffusion May Based Oct Segmentation, 2012 11th International Conference on Information Science, Signal Processing and their Applications, ISSPA 2012 (2012)
24. Vessel-Based Registration of Fundus and Optical Coherence Tomography Projection Images of Retina Using a Quadratic Registration Model, IET Image Processing (2013)
25. Hybrid Registration of Retinal Fluorescein Angiography and Optical Coherence Tomography Images of Patients With Diabetic Retinopathy, Biomedical Optics Express (2021)
26. Three-Dimensional Optical Coherence Tomography Image Denoising Through Multi-Input Fully-Convolutional Networks, Computers in Biology and Medicine (2019)
27. Classification of Dry Age-Related Macular Degeneration and Diabetic Macular Oedema From Optical Coherence Tomography Images Using Dictionary Learning, IET Image Processing (2020)
28. Formation and Fusion of Projection Images From 11 Layers of Retina Using Statistical Indicators to Obtain an Image With Appropriate Contrast From the Retinal Depth, Journal of Isfahan Medical School (2013)
29. Forming Optimal Projection Images From Intra-Retinal Layers Using Curvelet-Based Image Fusion Method, Journal of Medical Signals and Sensors (2020)
30. Curvature Correction of Retinal Octs Using Graph-Based Geometry Detection, Physics in Medicine and Biology (2013)
31. X-Let's Atom Combinations for Modeling and Denoising of Oct Images by Modified Morphological Component Analysis, IEEE Transactions on Medical Imaging (2024)
32. 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)
33. Video Denoising in Three-Dimensional Complex Wavelet Domain Using a Doubly Stochastic Modelling, IET Image Processing (2012)
34. 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)
35. Intra-Retinal Layer Segmentation of 3D Optical Coherence Tomography Using Coarse Grained Diffusion Map, Medical Image Analysis (2013)
36. Obtaining Thickness Maps of Corneal Layers Using the Optimal Algorithm for Intracorneal Layer Segmentation, International Journal of Biomedical Imaging (2016)
37. 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)
38. 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)
39. Synthetic Oct Data in Challenging Conditions: Three-Dimensional Oct and Presence of Abnormalities, Medical and Biological Engineering and Computing (2022)
40. Wavelet-Domain Medical Image Denoising Using Bivariate Laplacian Mixture Model, IEEE Transactions on Biomedical Engineering (2009)
41. Comparison of Macular Octs in Right and Left Eyes of Normal People, Progress in Biomedical Optics and Imaging - Proceedings of SPIE (2014)
42. Retinal Oct Texture Analysis for Differentiating Healthy Controls From Multiple Sclerosis (Ms) With/Without Optic Neuritis, BioMed Research International (2021)
43. Intra-Retinal Layer Segmentation of Optical Coherence Tomography Using Diffusion Map, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (2013)
44. Isfahan Artificial Intelligence Event 2023: Macular Pathology Detection Competition, Journal of Medical Signals and Sensors (2025)
45. Automatic Classification of Retinal Three-Dimensional Optical Coherence Tomography Images Using Principal Component Analysis Network With Composite Kernels, Journal of Biomedical Optics (2017)
46. Analysis of a Novel Segmentation Algorithm for Optical Coherence Tomography Images Based on Pixels Intensity Correlations, IEEE Transactions on Instrumentation and Measurement (2021)
47. 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)
48. Segmentation of Choroidal Boundary in Enhanced Depth Imaging Octs Using a Multiresolution Texture Based Modeling in Graph Cuts, Computational and Mathematical Methods in Medicine (2014)
49. A New Texture-Based Segmentation Method for Optical Coherence Tomography Images, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (2019)
50. Automatic Production of Synthetic Labelled Oct Images Using an Active Shape Model Hajar Danesh, IET Image Processing (2020)