%0 Journal Article %1 noauthororeditor %A Ahmed, S. Thilagavathi Dr. M. S. Irfan %D 2017 %J International Journal of Trend in Scientific Research and Development %K KNN Mammography Preprocessing SVM %N 1 %P 1210-1214 %T Mass Detection and Classification System for Mammography Image Preprocessing %U http://www.ijtsrd.com/medicine/other/8223/mass-detection-and-classification-system-for-mammography-image-preprocessing/s-thilagavathi %V 2 %X Today in the entire world in numerous territories, Breast malignancy is a main source of disease especially in lady in which most normal bosom anomalies are masses and calcifications. Early location of determination is the way to bosom malignancy controls that expansion the accomplishment of treatment, spare lives and diminish cost. It is troublesome for the radiologist to perceive the majority on a mammogram since they are encompassed by muddled tissues, thus numerous frameworks have been produced to help the radiologist in distinguishing mammography injuries that may demonstrate the nearness of bosom disease. The exploratory outcomes demonstrate that the proposed CAD framework enormously enhances the five target records in correlation with mass recognition and characterizations framework for mammography picture preprocessing. S. Thilagavathi | Dr. M. S. Irfan Ahmed"Mass Detection and Classification System for Mammography Image Preprocessing" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-1 , December 2017, URL: http://www.ijtsrd.com/papers/ijtsrd8223.pdf http://www.ijtsrd.com/medicine/other/8223/mass-detection-and-classification-system-for-mammography-image-preprocessing/s-thilagavathi

@article{noauthororeditor, abstract = {Today in the entire world in numerous territories, Breast malignancy is a main source of disease especially in lady in which most normal bosom anomalies are masses and calcifications. Early location of determination is the way to bosom malignancy controls that expansion the accomplishment of treatment, spare lives and diminish cost. It is troublesome for the radiologist to perceive the majority on a mammogram since they are encompassed by muddled tissues, thus numerous frameworks have been produced to help the radiologist in distinguishing mammography injuries that may demonstrate the nearness of bosom disease. The exploratory outcomes demonstrate that the proposed CAD framework enormously enhances the five target records in correlation with mass recognition and characterizations framework for mammography picture preprocessing. S. Thilagavathi | Dr. M. S. Irfan Ahmed"Mass Detection and Classification System for Mammography Image Preprocessing" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-1 , December 2017, URL: http://www.ijtsrd.com/papers/ijtsrd8223.pdf http://www.ijtsrd.com/medicine/other/8223/mass-detection-and-classification-system-for-mammography-image-preprocessing/s-thilagavathi }, added-at = {2018-09-01T14:37:33.000+0200}, author = {Ahmed, S. Thilagavathi Dr. M. S. Irfan}, biburl = {https://www.bibsonomy.org/bibtex/253e0051dc2befa4223f6dc5d0e3a72d0/ijtsrd}, interhash = {e9a5c511a01bb6b8326a2361848d69ff}, intrahash = {53e0051dc2befa4223f6dc5d0e3a72d0}, issn = {2456-6470}, journal = {International Journal of Trend in Scientific Research and Development}, keywords = {KNN Mammography Preprocessing SVM}, language = {English}, month = dec, number = 1, pages = {1210-1214}, timestamp = {2018-10-02T11:01:27.000+0200}, title = {Mass Detection and Classification System for Mammography Image Preprocessing }, url = {http://www.ijtsrd.com/medicine/other/8223/mass-detection-and-classification-system-for-mammography-image-preprocessing/s-thilagavathi}, volume = 2, year = 2017 }