WAVELET BASED SEGMENTATION USING OPTIMAL STATISTICAL FEATURES ON BREAST IMAGES

Elastography is the emerging imaging modality that analyzes the stiffness of the tissue for detecting and classifying breast tumors. Computer-aided detection speeds up the diagnostic process of breast cancer improving the survival rate. A multiresolution approach using Discrete wavelet transform is...

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Bibliographic Details
Published inICTACT journal on image and video processing Vol. 4; no. 4; pp. 853 - 857
Main Authors A, Sindhuja, V, Sadasivam
Format Journal Article
LanguageEnglish
Published ICT Academy of Tamil Nadu 01.05.2014
Subjects
Artificial Neural Networks
Feature Extraction
FPGA
Image Recognition
Spiking Neuron
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Summary:Elastography is the emerging imaging modality that analyzes the stiffness of the tissue for detecting and classifying breast tumors. Computer-aided detection speeds up the diagnostic process of breast cancer improving the survival rate. A multiresolution approach using Discrete wavelet transform is employed on real time images, using the low-low (LL), low-high (LH), high-low (HL), and high-high (HH) sub-bands of Daubechies family. Features are extracted, selected and then finally segmented by K-means clustering algorithm. The proposed work can be extended to Classification of the tumors.
ISSN:0976-9099
0976-9102
DOI:10.21917/ijivp.2014.0123