Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Empirical evaluation of dissimilarity measures for color and texture
Computer Vision and Image Understanding - Special issue on empirical evaluation of computer vision algorithms
Novel Histogram Processing for Colour Image Enhancement
ICIG '04 Proceedings of the Third International Conference on Image and Graphics
Neural Networks - 2005 Special issue: IJCNN 2005
Pattern Recognition, Fourth Edition
Pattern Recognition, Fourth Edition
Feature selection with complexity measure in a quadratic programming setting
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Robust predictive model for evaluating breast cancer survivability
Engineering Applications of Artificial Intelligence
The data replication method for the classification with reject option
AI Communications
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Objective: This work presents a novel approach for the automated prediction of the aesthetic result of breast cancer conservative treatment (BCCT). Cosmetic assessment plays a major role in the study of BCCT. Objective assessment methods are being preferred to overcome the drawbacks of subjective evaluation. Methodology: The problem is addressed as a pattern recognition task. A dataset of images of patients was classified in four classes (excellent, good, fair, poor) by a panel of international experts, providing a gold standard classification. As possible types of objective features we considered those already identified by domain experts as relevant to the aesthetic evaluation of the surgical procedure, namely those assessing breast asymmetry, skin colour difference and scar visibility. A classifier based on support vector machines was developed from objective features extracted from the reference dataset. Results: A correct classification rate of about 70% was obtained when categorizing a set of unseen images into the aforementioned four classes. This accuracy is comparable with the result of the best evaluator from the panel of experts. Conclusion: The results obtained are rather encouraging and the developed tool could be very helpful in assuring objective assessment of the aesthetic outcome of BCCT.