DocumentCode
3413572
Title
A novel mammographic mass detection approach to combining suprevised and unsuprevised detection algorithms
Author
Dae Hoe Kim ; Jae Young Choi ; Yong Man Ro
Author_Institution
Image & Video Syst. Lab., Korea Adv. Inst. of Sci. & Technol. (KAIST), Daejeon, South Korea
fYear
2012
fDate
Sept. 30 2012-Oct. 3 2012
Firstpage
2857
Lastpage
2860
Abstract
In this paper, we propose the combination of different mass detection algorithms to increase overall mass detection sensitivity for various types of breast masses on mammograms. In particular, supervised and unsupervised mass detection algorithms are effectively combined to maximize complementary effects of both approaches. By combining the aforementioned mass detection algorithms, we can arrive at a combined mass detection approach that makes stronger and accurate detection results. Comparative experiments have been conducted on public mammogram data set. Our results show that the proposed detection system can considerably improve the mass detection sensitivity with relatively small number of false positives, compared to the implementation of using only a single detection solution.
Keywords
cancer; mammography; medical image processing; object detection; mammographic mass detection; mass detection sensitivity; unsuprevised detection algorithms; Breast; Cancer; Databases; Delta-sigma modulation; Detection algorithms; Sensitivity; Shape; Mammography; breast masses; combination; multiple detection; supervised and unsupervised mass detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing (ICIP), 2012 19th IEEE International Conference on
Conference_Location
Orlando, FL
ISSN
1522-4880
Print_ISBN
978-1-4673-2534-9
Electronic_ISBN
1522-4880
Type
conf
DOI
10.1109/ICIP.2012.6467495
Filename
6467495
Link To Document