| Paper Details: | Downloads: 796 |
| Serial Number: | P1151209133
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| Title: | Effective Detection of cancerous masses in mammogram using COBWEB technique
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| Authors: | S.Pitchumani Angayarkanni and Dr.Nadira Banu Kamal
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| Abstract: | Breast cancer is one of the most common form of cancer in women. In order to reduce the death rate , early detection of cancerous regions in mammogram images is needed. The existing system is not so accurate and it is time consuming one. The system we propose includes the data mining concept for early, fast and accurate detection of cancerous masses in mammogram images[1]. The system we propose consists of :preprocessing phase, a phase for segmenting normal, benign and malignant regions and a phase for mining the resulted traditional Database and a final phase of the classification as benign, malignant and normal based on COBWEB analysis technique .The stages are predicted based on the attributes selected from COBWEB Analysis. The experimental results show that the method performs well, reaching over 99% accuracy compared to other existing technqiues. This is mainly to increase the levels of diagnostic confidence and to provide immediate second opinion for physician.
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| Keywords: | Preprocessing, Gabor Filter,Texture analysis,SOM based Visualization,COBWEB method
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| Journal/Conference: | ICGST International Conference on Computer Science and Engineering, CSE-Dubai-12
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| Submission Date: | 3/1/2012 12:00:00 AM
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| Review Date: | 4/9/2012 12:00:00 AM
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| Publishing Date: | 7/16/2012 12:00:00 AM
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| Article Downloads: | 796
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