Classification of benign and malignant breast tumors based on hybrid level set segmentation
Improved GA and CNN provided level set with more efficient initial boundaries compared to SFC. Level set parameters were tuned using a dynamic training procedure adaptively and automatically. MLP produces the highest classification accuracy among other classifiers. Adaptive segmentation methods achieved higher performance than that of the first proposed methods.
region growing cellular neural network level set method genetic algorithm memetic algorithm artificial neural network