SU‐GG‐I‐95: Simpler and Faster Watershed Medical Image Segmentation Algorithm

Abstract

Purpose: A watershed medical image segmentation method has a drawback of producing a region for each local minimum, resulting in oversegmentation. To alleviate this problem, a post merging process such as a hybrid graph merging algorithm is used, which impedes interactive segmentation with a graphical user interface. An effective watershed algorithm without a post merging process is proposed. Method and Materials: Our algorithm, as the preprocessing, includes the edge‐preserving noise reduction and gradient‐based boundary sharpening steps. Because the initial oversegmentation depends on the gradient image intensity variations, the noise reduction algorithm can reduce the problem appreciably. A well‐known statistical edge‐preserving noise reduction algorithm is implemented to preserve the boundaries of the image objects which have different physiological properties. Gradient‐based boundary sharpening stage follows the novel edge‐preserving noise reduction step. Boundary sharpening process combined with watershed segmentation results in an effective watershed algorithm without a post merging process. The combination of the standard gradient values with two cross operators makes the edges sharper and thinner. A threshold value is controlled interactively with a steppedup graphical user interface in the boundary sharpening process. Results: We applied the method to both CT and MR images. Interactive real time medical image segmentation was possible with a graphical user interface. Threshold values were manipulated interactively with a mouse to get an appropriate segmentation of the abdomen CT image. It was also confirmed that this method produced the same segmentations as those of hybrid‐merging algorithm for the MR brain images. Conclusion: In the gradient‐based watershed, computing time is negligible and storage requirement can be reduced appreciably because a post hybrid merging algorithm is not necessary. Moreover, interactive real time segmentation is possible with the steppedup graphical user interface.