Medical ultrasound image segmentation algorithm based on SEEDS
To solve the problem of rapid recognition and automatic localization of tumors in High Intensity Focused Ultrasound(HIFU)therapy,an automatic segmentation method based on Superpixels Extracted via Energy-Driven Sampling(SEEDS)is proposed,which can help doctors locate the tumor quickly and accu-rately,and reduce the workload greatly.This segmentation method is based on the split-and-merge frame-work.Firstly,SEEDS algorithm is used to split the image into many superpixels.Then,the texture and boundary information of superpixels are extracted,and the texture boundary coding compression algorithm is used to complete the merging of superpixels.At last,the automatic segmentation of the tumor can be real-ized under the limitation of priori information.Experiment results show that the algorithm can deal with the problem of tumor segmentation in different situations such as low image quality and complex background,and get more accurate segmentation results.
superpixelsultrasound image segmentationtexture and boundaries codinguterine fibroids image
万方数据
维普
