S.Pitchumani Angayarkanni, Nadira Banu Kamal & V.Thavavel
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COMPARISON OF EXISTING WITH PROPOSED TECHNIQU Filters Used Median Filter
LowPass Filter Highpass filter Partial low and high pass filters Spatial and frequency domain filters Proposed Method Gabor Filter with histogram equalization
Features & Limitations Used to smooth the non repulsive noise from two-dimensional signals without blurring edges and preserve image details. Suitable for enhancing mammogram images. Pectoral muscles are not detected Reduces noise and also blurs the edges Enhances the details of the image Best Quality image is achieved
Used for image enhancement alone
Features 路 It acts as a local band-pass filter with optimal number of orientations and the scales define the number of filters that should affect input images by multiplying them with each other. 路 The joint localization properties of the image is enhanced by histogram equalization in the spatial and in the spatial frequency domain. It is used for detecting a first set of potential microcalcifications and elongated structures are identified 路 It also detects clusters of microcalcifications to extract textural features of an image
TEXTURE BASED APPROACH AND SOM BASED VISUALIZATION Texture based segmentation is implemented because for a person affected by cancer the texture of the skin becomes smooth. This segmentation method segments the calcification pattern and the other suspicious regions in the mammograms The GLCM image is divided into 3x3 matrix and the texture features are calculated[2,3]. Texture features are: Cluster prominence,Energy,Entropy,Homogenity,Difference variance, Difference Entropy, Information Measure, Normalized ,Correlation. Using GLCM (Gray Level Co-Occurrence Matrix) technique, the different combinations of brightness values that occur on the texture segmented image is found. Usually the GLCM matrix is found for small windows but in this project the GLCM matrix is found for the whole image. Then the GLCM Matrix is divided into small windows of size 3x3. Since the size of the Mammogram is larger, the size of the image is resized to 17x17 and the GLCM matrix gets segmented into 289 images. GLCM features: Cor-relation, Cluster Prominence, Energy, Entropy, Homogeneity, Difference Variance, Difference Entropy and Information Measure related to Cor-relation, and Normalized are calculated and stored in an Excel file.The texture values for 121 pairs of Mammogram MRI images are calculated and are stored in an excel sheet and it is analysed using SOM based Visualization technique .