Title :
Methods for clustered microcalcifications detection in digital mammograms
Author :
Diyana, Wan Mimi ; Besar, Rosli
Author_Institution :
Fac. of Eng., Multimedia Univ., Selangor, Malaysia
Abstract :
This paper presents the comparison of three methods for clustered microcalcifications (MCCs) detection, which are associated with a high probability of malignancy. The proposed methods are morphological approach, fractal analysis and high-order statistics (HOS) test. We apply these methods on two sets of digital mammograms (MIAS database and McGill University database) to test their efficiency, accuracy and reliability in MCCs detection. Statistical analysis using receiver operating characteristics (ROC) curves and mean areas under the ROC curves are used in evaluating the performance of detection methods. It shows that the HOS test proved to be the most efficient and accurate and give reliable results for every mammogram tested.
Keywords :
fractals; higher order statistics; mammography; medical image processing; sensitivity analysis; tumours; visual databases; HOS test; MCC; ROC curves; clustered microcalcification detection; digital mammograms; fractal analysis; high-order statistics; image database; malignancy; morphological approach; probability; receiver operating characteristic; statistical analysis; Breast cancer; Cancer detection; Electronic mail; Fractals; Gray-scale; Image databases; Image processing; Statistical analysis; Telemedicine; Testing;
Conference_Titel :
Signal Processing and Information Technology, 2004. Proceedings of the Fourth IEEE International Symposium on
Print_ISBN :
0-7803-8689-2
DOI :
10.1109/ISSPIT.2004.1433681