Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
A Parametric Texture Model Based on Joint Statistics of Complex Wavelet Coefficients
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: modeling, learning, sampling and computing, Part I
Computer Vision and Fuzzy-Neural Systems
Computer Vision and Fuzzy-Neural Systems
Automated image analysis techniques for digital mammography
Automated image analysis techniques for digital mammography
Midpoints for fuzzy sets and their application in medicine
Artificial Intelligence in Medicine
Neuro-fuzzy rule generation: survey in soft computing framework
IEEE Transactions on Neural Networks
A self-organizing feature map-driven approach to fuzzy approximate reasoning
Expert Systems with Applications: An International Journal
Integrated Computer-Aided Engineering
Mammographic case base applied for supporting image diagnosis of breast lesion
Expert Systems with Applications: An International Journal
Contourlet-based mammography mass classification using the SVM family
Computers in Biology and Medicine
A comparison of wavelet and curvelet for breast cancer diagnosis in digital mammogram
Computers in Biology and Medicine
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
ICCVG'10 Proceedings of the 2010 international conference on Computer vision and graphics: Part I
Novel mean-shift based histogram equalization using textured regions
Expert Systems with Applications: An International Journal
Computers in Biology and Medicine
Diagnosing Breast Masses in Digital Mammography Using Feature Selection and Ensemble Methods
Journal of Medical Systems
Expert Systems with Applications: An International Journal
Ontology-based mammography annotation and Case-based Retrieval of breast masses
Expert Systems with Applications: An International Journal
Contourlet-based mammography mass classification
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Wavelet Analysis in Current Cancer Genome Research: A Survey
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Hi-index | 12.07 |
The high incidence of breast cancer in women has increased significantly in the recent years. The most familiar breast tumors types are mass and microcalcification. Mammograms-breast X-ray-are considered the most reliable method in early detection of breast cancer. Computer-aided diagnosis system can be very helpful for radiologist in detection and diagnosing abnormalities earlier and faster than traditional screening programs. Several techniques can be used to accomplish this task. In this paper, two techniques are proposed based on wavelet analysis and fuzzy-neural approaches. These techniques are mammography classifier based on globally processed image and mammography classifier based on locally processed image (region of interest). The system is classified normal from abnormal, mass for microcalcification and abnormal severity (benign or malignant). The evaluation of the system is carried out on Mammography Image Analysis Society (MIAS) dataset. The accuracy achieved is satisfied.