Paper Info
Title
Snakules: A Model-Based Active Contour Algorithm for the Annotation of Spicules on Mammography.
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.
Year
DOI
Venue
2010
10.1109/TMI.2010.2052064
IEEE Trans. Med. Imaging
Keywords
Field
DocType
pixel,observational study,spicules,active contour,sensitivity,algorithm design and analysis,snakes,image analysis
Active contour model,Mammography,Computer vision,Algorithm design,Annotation,Algorithm,Spiculated mass,Local matching,Pixel,Artificial intelligence,Observer (quantum physics),Mathematics
Journal
Volume
Issue
ISSN
29
10
0278-0062
Citations 
PageRank 
References 
10
0.69
14
Authors
8
Name
Order
Citations
PageRank
Gautam S. Muralidhar1163.27
Alan Conrad Bovik2228475.56
J. David Giese3100.69
Mehul P. Sampat418912.30
Gary J. Whitman5435.76
Tamara Miner Haygood6142.98
Tanya W. Stephens7152.54
Mia K. Markey835333.66