DocumentCode
1652138
Title
Detections of Microcalcification Clusters Using Multiple Mammographic Views
Author
Li, Ma ; Shan Yajing
Author_Institution
Sch. of Autom., Hangzhu Dianzi Univ., Hangzhou
fYear
2008
Firstpage
361
Lastpage
365
Abstract
To reduce the false positive hits, a new method for the computer aided detection of microcalcification clusters is proposed in the paper by joint analysis of two views of the same breast. The novelty of the scheme includes a consequent two steps of matching processes: spatial and feature matching. The former links a suspicious cluster located on the MLO view with a corresponding location on the CC view using their spatial information to form a paired cluster, and then in the latter stage, each cluster candidates are characterized by its single-view features such as size, shape and intensity. Finally a similarity function is calculated between the pair to determine if they were true microcalcification clusters. The experiments show that the proposed method has advantages of lower FP rate compared to the one on a single view.
Keywords
biological organs; feature extraction; image matching; image segmentation; mammography; medical image processing; CC view; MLO view; breast; computer aided detection; feature matching; mammographic view; microcalcification cluster detection; spatial matching; Automation; Breast cancer; Cancer detection; Computer vision; Detection algorithms; Feature extraction; Fractals; Multi-layer neural network; Neural networks; Shape;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4244-1747-6
Electronic_ISBN
978-1-4244-1748-3
Type
conf
DOI
10.1109/ICBBE.2008.92
Filename
4534972
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