Isfahan University of Medical Sciences

Science Communicator Platform

Stay connected! Follow us on X network (Twitter):
Share this content! On (X network) By
Optical Oherence Tomography Image Reconstruction Using Morphological Component Analysis Publisher Pubmed



Mokhtari M1 ; Daneshmand PG1 ; Rabbani H2
Authors
Show Affiliations
Authors Affiliations
  1. 1. Stud. Research Committee, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, 8174673461, Iran
  2. 2. Medical Image Signal Processing Research Center, Isfahan University of Medical Sciences, Isfahan, 8174673461, Iran

Source: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS Published:2019


Abstract

In this paper, we apply combination of sparse representations and a total variation for reconstruction of retinal optical coherence tomography (OCT) images. The OCT imaging is based on interferometry, therefore OCT images suffer from the existence of a high level of noise. Utilization of effective interpolation and denoising algorithms are necessary to reconstruct high-resolution OCT images, especially when the subsampling of data is done during acquisition. In this paper, we take total variational and Morphological Component Analysis (MCA) techniques to reduce noise and interpolate missing data. Different over-complete dictionaries are constructed by using curvelet transform, wavelet transform or DCT, which represent the texture and cartoon layers in B-scans. Comparative analysis of image interpolation is done by two combinations of dictionaries, which are (DCT+Curvelet) and (DWT+Curvelet) transforms. Layered structures are more distinguished in reconstructed image with curvelet dictionary and textures are mostly detectable by wavelet or DCT. Evaluations are done both visually and in terms of different performance measures. Our simulation results show that the (DCT+Curvelet) combination preserve the texture of the image well and the (DWT+Curvelet) combination has better performance in structure preservation. © 2019 IEEE.
Related Docs
View other Related Docs
1. Super-Resolution of Optical Coherence Tomography Images by Scale Mixture Models, IEEE Transactions on Image Processing (2020)
2. X-Let's Atom Combinations for Modeling and Denoising of Oct Images by Modified Morphological Component Analysis, IEEE Transactions on Medical Imaging (2024)
3. Optical Coherence Tomography Retinal Image Reconstruction Via Nonlocal Weighted Sparse Representation, Journal of Biomedical Optics (2018)
4. Combining Non-Data-Adaptive Transforms for Oct Image Denoising by Iterative Basis Pursuit, Proceedings - International Conference on Image Processing, ICIP (2022)
5. Three-Dimensional Curvelet-Based Dictionary Learning for Speckle Noise Removal of Optical Coherence Tomography, Biomedical Optics Express (2020)
6. Speckle Noise Reduction in Optical Coherence Tomography Using Two-Dimensional Curvelet-Based Dictionary Learning, Journal of Medical Signals and Sensors (2017)
7. Three Dimensional Data-Driven Multi Scale Atomic Representation of Optical Coherence Tomography, IEEE Transactions on Medical Imaging (2015)
8. Tensor Ring Decomposition Guided Dictionary Learning for Oct Image Denoising, IEEE Transactions on Medical Imaging (2024)
Experts (# of related papers)
View all Related Experts
Hossein Rabbani (76)
Raheleh Kafieh (28)
Other Related Docs
9. Reconstruction of Optical Coherence Tomography Images Using Mixed Low Rank Approximation and Second Order Tensor Based Total Variation Method, IEEE Transactions on Medical Imaging (2021)
10. Curvature Correction of Retinal Octs Using Graph-Based Geometry Detection, Physics in Medicine and Biology (2013)
11. Total Variation Regularized Tensor Ring Decomposition for Oct Image Denoising and Super-Resolution, Computers in Biology and Medicine (2024)
12. Super-Resolution of Retinal Optical Coherence Tomography Images Using Statistical Modeling, Journal of Medical Signals and Sensors (2024)
13. Mixed Multiscale Bm4d for Three-Dimensional Optical Coherence Tomography Denoising, Computers in Biology and Medicine (2023)
14. Optical Coherence Tomography Image Denoising Using Gaussianization Transform, Journal of Biomedical Optics (2017)
15. Forming Optimal Projection Images From Intra-Retinal Layers Using Curvelet-Based Image Fusion Method, Journal of Medical Signals and Sensors (2020)
16. 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)
17. Optimal Deep Learning Architecture for Automated Segmentation of Cysts in Oct Images Using X-Let Transforms, Diagnostics (2023)
18. Automatic Detection of Hyperreflective Foci in Optical Coherence Tomography B-Scans Using Morphological Component Analysis, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (2017)
19. 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)
20. Bandlets on Oriented Graphs: Application to Medical Image Enhancement, IEEE Access (2019)
21. Intra-Retinal Layer Segmentation of 3D Optical Coherence Tomography Using Coarse Grained Diffusion Map, Medical Image Analysis (2013)
22. Intra-Retinal Layer Segmentation of Optical Coherence Tomography Using 3D Fully Convolutional Networks, Proceedings - International Conference on Image Processing, ICIP (2018)
23. 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)
24. Three-Dimensional Segmentation of Retinal Cysts From Spectral-Domain Optical Coherence Tomography Images by the Use of Three-Dimensional Curvelet Based K-Svd, Journal of Medical Signals and Sensors (2016)
25. Vessel-Based Registration of Fundus and Optical Coherence Tomography Projection Images of Retina Using a Quadratic Registration Model, IET Image Processing (2013)
26. Automatic Choroidal Segmentation in Optical Coherence Tomography Images Based on Curvelet Transform and Graph Theory, Journal of Medical Signals and Sensors (2023)
27. A Review on Texture-Based Methods for Anomaly Detection in Retinal Optical Coherence Tomography Images, Optik (2023)
28. 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)
29. A New Convolutional Neural Network Based on Combination of Circlets and Wavelets for Macular Oct Classification, Scientific Reports (2023)
30. Three-Dimensional Optical Coherence Tomography Image Denoising Through Multi-Input Fully-Convolutional Networks, Computers in Biology and Medicine (2019)
31. Geometrical X-Lets for Image Denoising, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (2019)
32. Multivariate Statistical Modeling of Retinal Optical Coherence Tomography, IEEE Transactions on Medical Imaging (2020)
33. The Improvement of Extraction Retinal Pigment Epithelium (Rpe) Layer in Optical Coherence Tomography (Oct) Images by Using Piecewise Dynamic Programming Method in Patients With Persistent Epithelial Defect (Ped), Journal of Isfahan Medical School (2021)
34. 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)
35. Classification of Dry Age-Related Macular Degeneration and Diabetic Macular Oedema From Optical Coherence Tomography Images Using Dictionary Learning, IET Image Processing (2020)
36. Dual-Tree Complex Wavelet Input Transform for Cyst Segmentation in Oct Images Based on a Deep Learning Framework, Photonics (2023)
37. Wavelet Scattering Transform Application in Classification of Retinal Abnormalities Using Oct Images, Scientific Reports (2023)
38. Directional Analysis of Intensity Changes for Determining the Existence of Cyst in Optical Coherence Tomography Images, Scientific Reports (2022)
39. 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)
40. Reconstruction of Connected Digital Lines Based on Constrained Regularization, IEEE Transactions on Image Processing (2022)
41. 3D Curvelet-Based Segmentation & Quantification of Drusen in Optical Coherence Tomography Images, Journal of Electrical and Computer Engineering (2017)
42. Modeling of Retinal Optical Coherence Tomography Based on Stochastic Differential Equations: Application to Denoising, IEEE Transactions on Medical Imaging (2021)
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. Image Denoising Employing Local Mixture Models in Sparse Domains, IET Image Processing (2010)
46. Detection of Retinal Abnormalities in Oct Images Using Wavelet Scattering Network, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (2022)
47. A Matlab Package for Automatic Extraction of Flow Index in Oct-A Images by Intelligent Vessel Manipulation, SoftwareX (2020)
48. Automatic Detection of Microaneurysms in Oct Images Using Bag of Features, Computational and Mathematical Methods in Medicine (2022)
49. Retinal Optical Coherence Tomography Image Classification With Label Smoothing Generative Adversarial Network, Neurocomputing (2020)
50. Livelayer: A Semi-Automatic Software Program for Segmentation of Layers and Diabetic Macular Edema in Optical Coherence Tomography Images, Scientific Reports (2021)