The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Mammogram Classification Using Support Vector Machine
Abstract
Among the objectives of artificial intelligence techniques, we find computer-aided diagnosis systems that support preventive medical check-ups and perform detection, recognition, and classification patterns. Recently these techniques are emerged in different areas particularly in medical imaging. Medical image is an important source of information, and a golden tool for the diagnosis and assessment of a pathological analysis process. In this chapter Computer-Aided Diagnosis (CAD) system is proposed in detection and diagnosis of breast cancer, it is mainly composed of the following steps: preprocessing mammographic image, segmentation of suspect region on the mammographic image using Chan Vese model, extraction of global and local descriptors and then image classification into malignant and benign mammograms using Support Vector Machine (SVM) classifier. The analysis of mammographic images proposed system with a choice of the subset of local descriptors after tumor segmentation leads to a classification of malignant and benign mammograms. System proposed achieves 92% for accuracy.
Related Content
Jaime Salvador, Zoila Ruiz, Jose Garcia-Rodriguez.
© 2020.
12 pages.
|
Stavros Pitoglou.
© 2020.
11 pages.
|
Mette L. Baran.
© 2020.
13 pages.
|
Yingxu Wang, Victor Raskin, Julia M. Rayz, George Baciu, Aladdin Ayesh, Fumio Mizoguchi, Shusaku Tsumoto, Dilip Patel, Newton Howard.
© 2020.
15 pages.
|
Yingxu Wang, Lotfi A. Zadeh, Bernard Widrow, Newton Howard, Françoise Beaufays, George Baciu, D. Frank Hsu, Guiming Luo, Fumio Mizoguchi, Shushma Patel, Victor Raskin, Shusaku Tsumoto, Wei Wei, Du Zhang.
© 2020.
18 pages.
|
Nayem Rahman.
© 2020.
24 pages.
|
Amir Manzoor.
© 2020.
27 pages.
|
|
|