An applied research on improved watershed algorithm in medical image segmentation

作者：Hai Ben Zhai; Xie Rui Yun; Yuan Pei Yan

来源：International Journal of Signal Processing, Image Processing and Pattern Recognition, 2016, 9(11): 191-198.

DOI：10.14257/ijsip.2016.9.11.17

• Improved
• Initial segmentation
• K-means
• K-Means clustering algorithm
• Target identification
• Water-shed algorithm
• Watershed segmentation
• Watershed segmentation algorithm

The image segmentation technology is of great significance to the target identification. The watershed segmentation algorithm has wide application in image segmentation. The traditional watershed segmentation often causes the problems of over segmentation and noise sensitivity. Therefore, a medical image segmentation algorithm is proposed based on K-means clustering algorithm and improved watershed algorithm. First, K - means clustering algorithm is used for initial segmentation, and then the concept of similarity is put forward to improve the original watershed algorithm. Finally, the adjacent tiles of the initial segmentation is merged. The magnetic resonance image is regarded as the segmentation object. The experimental result shows that the proposed algorithm effectively solves the problem of the over-segmentation of traditional watershed algorithm, and achieves a satisfactory effect for the image segmentation.

• 出版日期2016
• 单位武汉理工大学