Detection of masses and microcalcifications in digital mammogram images using fuzzy logic
Article Category: Brief communication (Original)
Publié en ligne: 31 janv. 2017
Pages: 345 - 350
DOI: https://doi.org/10.5372/1905-7415.1004.497
Mots clés
© 2016 Mostafa Langarizadeh, Rozi Mahmud, Rafat Bagherzadeh
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
Background
Detection of small breast lesions is a challenging task for radiologists. Computer aided detection (CAD) systems are implemented to aid radiologists in detecting masses and microcalcifications. This has the potential to raise the level of sensitivity in breast cancer detection.
Objectives
To evaluate a new system to detect suggestions of suspicious small lesions.
Methods
Small samples were extracted from different tissue types. Texture features were calculated, and the best features were selected using Waikato Environment for Knowledge Analysis (WEKA) software. Subsequently, 7 selected features were used to form a decision tree. To reduce false negative cases, fuzzy logic was used. In the implementation phase, input images were divided into 8 pixel ´ 8 pixel tiles. For each tile, all selected features were computed as fuzzy inputs.
Results
To evaluate the technique, the suggested system was applied to 326 images obtained from the National Cancer Society of Malaysia. Based on this application, results showed that the suggested system has an acceptable sensitivity of 85.6% and specificity of 90.7%.
Conclusions
The fuzzy system is a promising technique for early detection of breast cancer.