FAST DETECTION OF MASSES IN MAMMOGRAMS WITH DIFFICULT CASE EXCLUSION
DOI:
https://doi.org/10.47839/ijc.4.3.365Keywords:
Mammography, Mass Detection, Image Processing, Computer-Aided DiagnosisAbstract
Breast cancer is one of the most common forms of cancer among women. Currently mammography is the most efficient method for early detection. A simple and fast mammographic mass detection system and two different methods for difficult case exclusion are presented in this paper. The mass detection system uses a modified version of a known algorithm for small masses and a new algorithm for large masses. The first difficult case filtering method is based on tissue density estimation, the second one on mass candidate count. The system was tested with 600 mammographic cases, each containing 4 images. Case-level performance was measured for malignant mass detection first without and then with difficult case exclusion.References
R. Highnam, M. Brady (Editors). Mammographic Image Analysis, Kluwer Academic Publishers, 1999.
S. Lee, P. Chung, C. Chang, C. Lo, T. Lee, G. Hsu, C. Yang. Classification of Clustered Microcalcifications Using a Shape Cognitron Neural Network. Neural Networks 16 (2003), pp. 121-132.
M. Altrichter, Z. Ludanyi, G. Horvath. Joint Analysis of Multiple Mammographic Views in CAD Systems for Breast Cancer Detection. Proceedings of the 14th Scandinavian Conference on Image Analysis (SCIA2005), Joensuu, Finland, 2005, pp. 760-769.
American College of Radiology. Illustrated Breast Imaging Reporting and Data System (BI-RADS) (3rd ed). Reston, VA: American College of Radiology, 1998.
M. D. Heath, K. W. Bowyer. Mass Detection by Relative Image Intensity. Proceedings of the Fifth International Workshop on Digital Mammography (IWDM-2000), Toronto, Canada, 2000, pp. 219-255.
M. D. Heath, K. W. Bowyer, D. Kopans. Current status of the Digital Database for Screening Mammography. Digital Mammography, Kluwer Academic Publishers, 1998, pp. 457-460.
G. Takacs, B. Pataki. Fast Detection of Mammographic Masses with Difficult Case Exclusion. Proceedings of the Third IEEE Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS’2005), Sofia, Bulgaria, 2005, pp. 424-428.
Downloads
Published
How to Cite
Issue
Section
License
International Journal of Computing is an open access journal. Authors who publish with this journal agree to the following terms:• Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
• Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
• Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.