Symmetry as a Continuous Feature
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiclass Spectral Clustering
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Shape Representation based on Integral Kernels: Application to Image Matching and Segmentation
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Integral Invariants for Shape Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
An introduction to ROC analysis
Pattern Recognition Letters - Special issue: ROC analysis in pattern recognition
The S-kernel: A measure of symmetry of objects
Pattern Recognition
IScIDE'11 Proceedings of the Second Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
Tensor based sparse decomposition of 3D shape for visual detection of mirror symmetry
Computer Methods and Programs in Biomedicine
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Shape characteristics of malignant and benign breast tumors are significantly different. In this paper, the reflective symmetry of breast tumor shapes on ultrasound images was investigated. A new reflective symmetry measure (RSML) derived from multiscale local area integral invariant was proposed to quantify the shape symmetry of breast tumor, which could be computed directly from the binary mask image without the shape parameterization in terms of arc length. The performance of several symmetry measures for differentiating malignant and benign breast tumors at varying scales was evaluated and compared by receiver operating characteristic (ROC) analysis. RSML with Gaussian kernel at scale 0.04 (related to the maximal diameter) achieved the highest area under the ROC curve (0.85) on the image data of 168 tumors (104 benign and 64 malignant). The experimental results showed that the reflective symmetry of breast tumor shape was capable of providing potential diagnostic information, which could be characterized quantitatively by RSML with the appropriate scale parameter.