Abstract
Speckle is an important noise in the optical coherence tomography (OCT) images that play a vital role in the degradation of the visual quality of images and makes it difficult to assess the quality of the images. In order to improve the quality, filtering is essential which removes the noises and reproduce the OCT images. This proposed work addresses various filters like Mean, Median, Adaptive Median, Gaussian, and Wiener in order to enhance the OCT image. This paper gives estimate of various filtering techniques on the basis of the performance indices calculated from the experimental results. The results of this research work suggest the filter suitable for OCT images depending on the Cross-Correlation, Mean Square Error-(MSE) and Peak Signal-to-Noise Ratio-(PSNR) which are very much used as performance indices in medical image applications and its analysis. Initially, the filter is tested with standard medical image and performance measures are calculated. Next, noise-corrupted OCT image is applied as an input to the filter for the purpose of denoising and finally, a comparative analysis was performed.
Keywords
- Biomedical image processing
- Image quality assessment
- Optical coherence tomography
- Speckle
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Acknowledgements
We would like to thank Dr. M. Ravishankar, director of the Nethralayam and Senior Consultant of the Rajan Eye Care Hospital, Chennai for providing the Optical Coherence Tomography Images.
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Saya Nandini Devi, M., Santhi, S. (2019). Enhancement of Optical Coherence Tomography Images: An Iterative Approach Using Various Filters. In: Pandian, D., Fernando, X., Baig, Z., Shi, F. (eds) Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB). ISMAC 2018. Lecture Notes in Computational Vision and Biomechanics, vol 30. Springer, Cham. https://doi.org/10.1007/978-3-030-00665-5_12
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DOI: https://doi.org/10.1007/978-3-030-00665-5_12
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