A Comparative Study of Speckle Reduction Filters for Ultrasound Images of Poly Cystic Ovary
G. Vasavi1, S. Jyothi2
1G. Vasavi, Research Scholar, Department of Computer Science, SPMVV, Tirupati (Andhra Pradesh), India.
2S. Jyothi, Department of Computer Science, Professor, SPMVV, Tirupati (Andhra Pradesh), India.
Manuscript received on 15 May 2019 | Revised Manuscript received on 19 May 2019 | Manuscript Published on 23 May 2019 | PP: 2084-2089 | Volume-7 Issue-6S5 April 2019 | Retrieval Number: F13740476S519/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Ultrasound imaging is the most commonly used modality in medical diagnosis and it is corrupted by speckle noise, which is multiplicative in nature. Hen cethere is a need to reduce the speckle noise in ultrasound images for a better diagnosis. In this paper we discuss and compare the performance of various speckle reduction filters namely Median, Wiener, Gaussian, Bilateral, Guided, Anisotropic Diffusion and Non-Local Means (NLM). Evaluation of the filters is done by considering different performance metrics for image quality such as Mean Square Error(MSE), Signal to Noise Ratio (SNR), Peak Signal to Noise Ratio(PSNR), Structural Similarity Index (SSIM) and determines the best suitabledespeckling filter for the ultrasound images of polycystic ovary.
Keywords: Ultrasound Images, Speckle Noise, Filtering Techniques, Image Quality Metrics, Polycysticovary.
Scope of the Article: Image Security