A Comparative Analysis of Different Despeckling Filters Using Breast Ultrasonographic Images
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Publisher
Springer Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-16-8774-7_34
Reference15 articles.
1. Virmani J, Agarwal R (2019) Assessment of despeckle filtering algorithms for segmentation of breast tumours from ultrasound images. Biocybern Biomed Eng 39(1):100–121
2. Dass R (2018) speckle noise reduction of ultrasound images using BFO cascaded with wiener filter and discrete wavelet transform in homomorphic region. ICCIDS-2018. Procedia Comput Sci 132:1543–1551
3. Dass R, Devi S (2012) Effect of Wiener-Helstrom filtering cascaded with bacterial foraging optimization to despeckle the ultrasound images. Int J Comput Sci Issues (IJCSI) 9(4):372–392
4. Devi S, Dass R (2011) Speckle noise reduction techniques. IJEEE 16(1):47–57
5. https://scholar.cu.edu.eg/?q=afahmy/pages/dataset. Accessed 20 Jan 2021
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2. Total variation‐based ultrasound image despeckling using method noise thresholding in non‐subsampled contourlet transform;International Journal of Imaging Systems and Technology;2023-01-24
3. Effect of Speckle Filtering in the Performance of Segmentation of Ultrasound Images Using CNNs;Communications in Computer and Information Science;2022
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