DocumentCode :
1511953
Title :
Snakules: A Model-Based Active Contour Algorithm for the Annotation of Spicules on Mammography
Author :
Muralidhar, Gautam S. ; Bovik, Alan C. ; Giese, J. David ; Sampat, Mehul P. ; Whitman, Gary J. ; Haygood, Tamara Miner ; Stephens, Tanya W. ; Markey, Mia K.
Author_Institution :
Dept. of Biomed. Eng., Univ. of Texas, Austin, TX, USA
Volume :
29
Issue :
10
fYear :
2010
Firstpage :
1768
Lastpage :
1780
Abstract :
We have developed a novel, model-based active contour algorithm, termed “snakules”, for the annotation of spicules on mammography. At each suspect spiculated mass location that has been identified by either a radiologist or a computer-aided detection (CADe) algorithm, we deploy snakules that are converging open-ended active contours also known as snakes. The set of convergent snakules have the ability to deform, grow and adapt to the true spicules in the image, by an attractive process of curve evolution and motion that optimizes the local matching energy. Starting from a natural set of automatically detected candidate points, snakules are deployed in the region around a suspect spiculated mass location. Statistics of prior physical measurements of spiculated masses on mammography are used in the process of detecting the set of candidate points. Observer studies with experienced radiologists to evaluate the performance of snakules demonstrate the potential of the algorithm as an image analysis technique to improve the specificity of CADe algorithms and as a CADe prompting tool.
Keywords :
diagnostic radiography; mammography; medical diagnostic computing; physiological models; CADe algorithms; CADe prompting tool; active contour algorithm; computer-aided detection; image analysis technique; mammography; snakules; spicules; Active contours; Biomedical measurements; Breast cancer; Engineering profession; Image converters; Image motion analysis; Lesions; Mammography; Permission; Statistics; Active contours; computer-aided detection; mammography; snakes; snakules; spicules; Algorithms; Breast Neoplasms; Calcinosis; Mammography; Pattern Recognition, Automated; Radiographic Image Enhancement; Radiographic Image Interpretation, Computer-Assisted; Reproducibility of Results; Sensitivity and Specificity;
fLanguage :
English
Journal_Title :
Medical Imaging, IEEE Transactions on
Publisher :
ieee
ISSN :
0278-0062
Type :
jour
DOI :
10.1109/TMI.2010.2052064
Filename :
5482212
Link To Document :
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