A Fuzzy Connectedness Segmentation of Image Sequences Based on 3D Seed Points Selection

Image segmentation is an essential and important part in medical image processing. Conventional methods typically demand significant amounts of time and don¿t lend to a natural interaction scheme with 3D volume. In this paper we present a novel interactive method for fuzzy connectedness segmentation. In our approach, the user freely specifies a seed point 3D location at regions of interest directly over the 3D volume. Then the 3D seed points will be mapped into seed pixels in some 2D slices of image-sequences. After that, the proposed algorithm is used to segmentation of multiple objects from complex background and batch segmentation of image sequences. That can be achieved by seeds picked from object and background in 3D volume. The experimental results with a serial of abdominal CT images show that the proposed method can improve the accuracy of segmentation effectively with very little interaction.