A Research on Computer Aided Detection System for Women Breast Cancer Diagnosis from Digital Mammographic Images
P. Malathi1, A. Kalaivani2
1P. Malathi, Assistant Professor, Department of CSE, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai (Tamil Nadu), India.
2A. Kalaivani, Associate Professor, Department of CSE, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai (Tamil Nadu), India.
Manuscript received on 13 October 2019 | Revised Manuscript received on 22 October 2019 | Manuscript Published on 02 November 2019 | PP: 1008-1014 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B11690982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1169.0982S1119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The Women breast cancer is the most critical cancer that are found in women. Its the second important cause of death in the world. Breast cancer has been ranked number one cancer in Indian females with rates occurrence of 25.8 per 1,00,000 females and death rate 12.7 among 1,00,000. Generally breast cancer is a malignant tumor that begins in the cells of the breast and eventually it spreads to the surrounding tissues. Early detection and diagnosis can reduce the mortality rate. Radiologist misdiagnosis the disease due to technical issues such as imaging quality and human error. Radiologists can improve the performance of Computer Aided Detection/Diagnosis (CAD) systems to finding and discriminating between the normal and abnormal tissues. Breast cancer diagnosis can applied are applied recent CAD systems on imaging modalities such as mammogram, ultrasound, MRI and biopsy histopathological images. CAD system have four stages for diagnosis which are pre-processing, segmentation, Feature Extraction and Classification. CAD system are developed to reduce the time taken to diagnose the breast cancer and reduce the death rate. This paper focus on the survey of CAD system to detect women breast cancer disease from the digital mammographic images to achieve high accuracy and low computational cost.
Keywords: Benign Tumor, Computer Aided Diagnosis (CAD), Digital Mammograms, Malignant Tumor.
Scope of the Article: Advanced Computer Networking