On Medical Image Segmentation Based on Wavelet Transform

The Image segmentation is the focus in the image processing technology all the time. Medical image segmentation is an important application in the field of image segmentation. Wavelet transform is proposed to segment medical image. Firstly the gray level histogram of the medical image was processed using multiscale wavelet transform. Then the gray threshold was gradually emerged by the performance from large scale factor to small scale factor. At last the difference of the effect between traditional method and wavelet transform method were compared. The experimental results showed that the last method surpasses the traditional one in image segmentation and the results has been demonstrated to have validity and practicability. Image segmentation can achieve the anatomical structures and other interesting information of a medical image automatically or semi-automatically, which is helpful on the medical diagnosis.

I. Introduction

The image segmentation plays an important role in the image processing, and it works between the low level and high level of image processing. Research on image segmentation algorithm has been paid attention to for more than ten years, but there is not a suitable segmentation method which satisfies all image segmentation. There exist some shortcomings in traditional methods and they cannot meet the requirements, bringing difficulties for further research.