Snakules: a model-based active contour algorithm for the annotation of spicules on mammography.
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.
Department of Biomedical Engineering, The University of Texas, Austin, TX 78172, USA. gautam@mail.utexas.edu
Gautam S
GS
Muralidhar
Alan C
AC
Bovik
J David
JD
Giese
Mehul P
MP
Sampat
Gary J
GJ
Whitman
Tamara Miner
TM
Haygood
Tanya W
TW
Stephens
Mia K
MK
Markey
D000465:Algorithms; D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000209:etiology*; D002114:Calcinosis / Q000150:complications* / Q000000981:diagnostic imaging*; D008327:Mammography / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity