Breast Cancer Detection and Classification | Matlab IEEE Image Processing Project

Breast Cancer Detection and Classification | Matlab IEEE Image Processing Project.
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IEEE Base Paper Title: Breast Cancer Detection and Classification.
Implementation: MATLAB.
Cost (In Indian Rupees): Rs.3000/.

IEEE Base paper Abstract:
Breast Cancer is more common hence, identification of BC and detection of region of breast affected is more important. Mammography screening images two views CC and MLO are widely use in diagnosis process. This paper presents the method to detect cancer region and classify normal and cancerous patient. Pre-processing operation perform on the input Mammogram image and undesirable part removed from the image, tumor region segmented from the image using morphological operation and highlighted the region on original mammogram image or if mammogram image is normal case then it shows that patient is normal. Random Forest (RF) classifiers is used for classification of BC patient and normal patient. Classification accuracy of RF is 95% for image of different patient. Processing time of RF classifier is 6.25s.

REFERENCE:
Poonam Kathale; Snehal Thorat, “Breast Cancer Detection and Classification”, 2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE), IEEE Conference, 2020.

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