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Title:: Brain CT image focus segmentation algorithm based on Prewitt algorithm

Author(s):: ZHANG Wenhui1; ZHAO Qiang2; 1. Department of Neurology，Baoding 7th Hospital of Hebei , Baoding 072150，China；2.Hebei University of Science and Technology, Shijiazhuang 050000，China

Keywords:: Prewitt algorithm; Intracranial; CT image; Focus; Segmentation algorithm

摘要:: 针对颅内CT图像病灶周围存在大量噪声，分割结果欠佳的问题，本研究提出基于Prewitt算法的颅内CT图像病灶分割算法。首先采用改进型中值小波去噪算法，去除颅内CT图像中的噪声点，优化图像质量；然后使用基于Prewitt算法的图像分割法，完成去噪后CT图像的病灶分割。结果表明，本研究算法在分割颅内CT图像病灶时，错分率为对比算法的1/10，并可将颅内CT图像的噪声点全部去除。说明该算法对颅内CT图像病灶的分割可行性，可用于颅内CT图像病灶分割。

Abstract:: Focus on a lot of noises around the lesions in CT images, and the segmentation results are not good，we proposed a segmentation algorithm based on Prewitt algorithm. Firstly, the denoising method of intracranial CT image based on the improved median wavelet was used to remove the noise points in the intracranial CT image and optimize the quality of the intracranial CT image; then we used the image segmentation method based on Prewitt algorithm to complete the focus segmentation of the intracranial CT image after denoising. The experimental results showed that the error rate of the proposed algorithm was 1 / 10 of the comparison algorithm, and all the noise points of the denoised intracranial CT image were removed. It is feasible for the segmentation of intracranial CT image lesions, and can be used in the segmentation of intracranial CT image lesions.