Abstract
|
Article Information:
Automated Abnormal Mass Detection in the Mammogram Images Using Chebyshev Moments
Alireza Talebpour, Dooman Arefan and Hamid Mohamadlou
Corresponding Author: Dooman Arefan
Submitted: May 13, 2012
Accepted: June 23, 2012
Published: January 11, 2013 |
Abstract:
|
Breast cancer is the second leading cause of cancer mortality among women after lung cancer. Early
diagnosis of this disease has a major role in its treatment. Thus the use of computer systems as a detection tool could
be viewed as essential to helping with this disease. In this study a new system for automated mass detection in
mammography images is presented as being more accurate and valid. After optimization of the image and extracting
a better picture of the breast tissue from the image and applying log-polar transformation, Chebyshev moments can
be calculated in all areas of breast tissue. Then after extracting effective features in the diagnosis of mammography
images, abnormal masses, which are important for the physician and specialists, can be determined with applying
the appropriate threshold. To check the system performance, images in the MIAS (Mammographic Image Analysis
Society) mammogram database have been used and the results allowed us to draw a FROC (Free Response Receiver
Operating Characteristic) curve. When compared the FROC curve with similar systems experts, the high ability of
our system was confirmed. In this system, images of different thresholds, specifically 445, 450, 455 are processed
and then put through a sensitivity analysis. The process garnered good results 100, 92 and 84%, respectively and a
false positive rate per image 2.56, 0.86, 0.26, respectively have been calculated. Comparing other automatic mass
detection systems, the proposed method has a few advantages over prior systems: Our process allows us to
determine the amount of false positives and/or sensitivity parameters within the system. This can be determined by
the importance of the detection work being done. The proposed system achieves 100% sensitivity and 2.56 false
positive for every image.
Key words: Automatic method, chebyshev moments, image processing, mammography, mass detection, ,
|
Abstract
|
PDF
|
HTML |
|
Cite this Reference:
Alireza Talebpour, Dooman Arefan and Hamid Mohamadlou, . Automated Abnormal Mass Detection in the Mammogram Images Using Chebyshev Moments. Research Journal of Applied Sciences, Engineering and Technology, (02): 513-518.
|
|
|
|
|
ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
|
Information |
|
|
|
Sales & Services |
|
|
|