The week's pick
Random Articles
Reseach Article
Detection of Breast Tumour and Speckle Noise Removal using Bilateral Filter and Bivariate Shrinkage
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 116 - Number 3 |
| Year of Publication: 2015 |
| Authors: Simi Wilson, M.thangamani, E.konguvel |
10.5120/20318-2383
|
Simi Wilson, M.thangamani, E.konguvel . Detection of Breast Tumour and Speckle Noise Removal using Bilateral Filter and Bivariate Shrinkage. International Journal of Computer Applications. 116, 3 ( April 2015), 42-45. DOI=10.5120/20318-2383
Abstract
Automated Breast Ultrasound (ABUS) is an image interpretation to detect the breast tumors. Tumor detection has become a challenging task, due to the presence of poor image contrast, speckle noise and irregular tumor shape. The scope of the work is to remove the speckle noise efficiently while preserving important information from the tumor boundaries. Bilateral filter and the Bivariate Shrinkage Function is applied to the automated whole breast ultrasonic image for the removal of speckle noise. A topographic watershed transform is implemented for ABUS image segmentation process where the précised contour of breast tumors is extracted automatically. This segmented lesion extracts various features like GLCM features, Tamura features, MCHOG features and shape features. Binary logistic regression classifier is applied to the selected feature vectors to analyze the tumor and non-tumor images.
References
- R. F. Chang, K. C. Chang-Chien, H. J. Chen, D. R. Chen, E. Takada,and W. K. Moon, "Whole breast computer-aided screening using free-hand ultrasound," in Int. Congr. Ser. , Jun. , vol. 1281, pp. 1075–1080.
- Xiangjun Shi, H. D. Cheng, Liming Hu (2006), "Mass Detection and Classification in Breast Ultrasound Images Using Fuzzy SVM" in JCIS ,pp 29-36
- Dina Aboul Dahab, Samy S. A. Ghoniemy, Gamal M. Selim," Automated Brain Tumor Detection and Identification Using Image Processing and Probabilistic Neural Network Techniques", International Journal of Image Processing and Visual Communication ISSN 2319-1724 : Volume (Online) 1 , Issue 2 , October 2012.
- Nalini Singh, Ambarish G Mohapatra," Breast Cancer Mass Detection in Mammograms using K-means and Fuzzy C-means Clustering", International Journal of Computer Applications (0975 – 8887) Volume 22– No. 2, May 2011.
- Moon. W. K, Lo. C. M, Chang J. M, Huang. C. S, Chen. J. H, and Chang R. F, (2012), "Computer-aided classification of breast masses using speckle features of automated breast ultrasound images," Med. Phys. , vol. 39, no. 10, pp. 6465–6473.
- A. D. Belsare and M. M. Mushrif, " Histopathological image analysis using image processing techniques: an overview", Signal & Image Processing : An International Journal (SIPIJ) Vol. 3, No. 4, August 2012.
- Gauri P. Anandgaonkar, Ganesh. S. Sable, "Detection and Identification of Brain Tumor in Brain MR Images Using Fuzzy C-Means Segmentation", International Journal of Advanced Research in Computer and Communication Engineering Vol. 2, Issue 10, October 2013.
- Tan . T, Platel. B, Mus. R, Tabar. L, Mann. R. M. and Karssemeijer. N, (2013), "Computer - aided detection of cancer in automated 3-D breast ultrasound," IEEE Trans. Med. Imag. , vol. 32, no. 9, pp. 1698–1706.
- K. Sankar, Dr. M. Prabakaran, "Region Based Mass Estimation Technique Based Image Segmentation for Lung Cancer Detection Using Gabor Filters", International Journal of Inventions in Computer Science and Engineering ISSN (Online): 2348 – 3539, ISSN (Print): 2348 – 3431 Volume 1 Issue 5 June 2014.
- Chung-ming lo, Rong-tai chen, Yeun-chung chang,Ya- wen yang, ming-jen hung, chiun- sheng huang, and ruey-feng chang, ( 2014) ,"multidimensional tumor detection in automated whole breast ultrasound using topographic watershed," IEEE transactions on medical imaging,vol. 33, pp. 1503-1511.
Index Terms
Keywords