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Title

Classification of Microcalcification Areas Based on Extraction Of Local Features From Breast Ultrasound images

Year: 1399
COI: TETSCONF05_012
Language: EnglishView: 158
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Authors

Mahshid Hemati Nik - Faculty of Science and Research University, Tehran, Iran
Nader Jafarnia Dabanloo - Faculty of Science and Research University, Tehran, Iran
Elham Keshavarz - Faculty of Shahid Beheshti University
Ensie Khalili - Faculty of Shahid Beheshti University

Abstract:

Breast calcification is the deposition of calcium in breast tissue.Mammographic images show these deposits as white dots or lines and areusually so small that they cannot be felt. Breast calcifications are usually seenon mammograms and are much easier to diagnose after menopause. Althoughthese calcifications are usually noncancerous (benign), certain patterns ofbreast calcification - such as tight clusters or abnormal shapes - can indicatebreast cancer. If the pattern of calcification is suspected, the radiologist willrecommend further tests such as re-mammography with magnified images orbreast biopsy or ultrasound. The best way to tell if a tissue is cancerous is touse a biopsy and then evaluate if the problem is that it is invasive.Mammography is currently the most appropriate way to diagnose breastcancer. However, due to the type of breast tissue and the use of low-density Xraysin mammograms, the images have low contrast. Tumors also havedifferent sizes and shapes, so it is very difficult and tedious to diagnose lesions,especially in the early stages of formation. The aim of this dissertation is toregionalize breast tissue and extract local features from it in order todistinguish calcified areas from non-calcified areas with higher accuracy andwith the help of a computer. The results for identifying places withcalcification and without it for the classification of support vector machinewith polynomial kernel have 100% accuracy, 96% sensitivity and 100%detection power, which shows the high potential of the proposed methodcompared to other articles .

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This Paper COI Code is TETSCONF05_012. Also You can use the following address to link to this article. This link is permanent and is used as an article registration confirmation in the Civilica reference:

https://civilica.com/doc/1142898/

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Hemati Nik, Mahshid and Jafarnia Dabanloo, Nader and Keshavarz, Elham and Khalili, Ensie,1399,Classification of Microcalcification Areas Based on Extraction Of Local Features From Breast Ultrasound images,5th International Conference on Innovative Technologies in Science, Engineering and Technology,https://civilica.com/doc/1142898

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