Pathological liver segmentation using stochastic resonance and cellular automata ?
We present a new method to segment low contrast liver CT images with high noise level. We utilize the noise constructively to enhance the input image contrast. The segmentation method is based on cellular automata. Level sets are used to generate segmentation of intermediate slices. The results show good segmentation accuracy when compared with ground truth images.
liver stochastic resonance ct image segmentation dynamic cellular automata graph cut contrast enhancement discrete gabor transform