Downloads: 129 | Weekly Hits: ⮙1 | Monthly Hits: ⮙1
Review Papers | Computer Science & Engineering | India | Volume 2 Issue 2, February 2013
Comparative Study of Wavelet Adaptive Windowing Method an Effective Technique for Tumor Detection in Mammilla (Bosom)
Jayashree R.Parate | R.K.Krishna
Abstract: Mammography is the study of the breast using x rays. The original l test is called a mammogram. It is an x ray of the breast which shows the fatty and glandular tissue. A diagnostic mammogram is for evaluation of abnormalities in women. The purpose of screening mammography is breast cancer detection. Mammography generally consists of two subsystems. One is a tumor-mass detection system and the other is a clustered-micro calcification detection system. In this paper, by using wavelet based adaptive windowing technique, the breast tumour can be highlighted. Techniques are goes under three progressive steps; Coarse segmentation, Fine segmentation and intensity adjustment. First step can be performed by using wavelet based histogram thresholding where, by using 1D wavelet based analysis, the threshold value is chosen. Fine segmentation can be done by segmenting the image into finite number of big and small windows then threshold value has been obtained by calculating the mean, maximum and minimum pixel values for the windows based on that threshold values the shady areas have been segmented. Preprocessing step is applied to improve the quality of an image before implementing the proposed technique. Mini MIAS database shows that the proposed technique is capable of detecting tumors of very graze shapes.
Keywords: wavelet based Thresholding, breast cancer, mammography, window based Thresholding, segmentation
Edition: Volume 2 Issue 2, February 2013,
Pages: 191 - 199
How to Cite this Article?
Jayashree R.Parate, R.K.Krishna, "Comparative Study of Wavelet Adaptive Windowing Method an Effective Technique for Tumor Detection in Mammilla (Bosom)", International Journal of Science and Research (IJSR), Volume 2 Issue 2, February 2013, pp. 191-199, https://www.ijsr.net/get_abstract.php?paper_id=IJSRON2013391
How to Share this Article?
Similar Articles with Keyword 'breast cancer'
Neural Systems Approach for Ammography Finding by Utilizing Wavelet Features
A. Mallareddy  | A. Priyanka
Breast Cancer Diagnosis and Prediction Using Machine Learning Algorithm