CT序列图像分割的分割及重建

Segmentation and Reconstruction of CT Sequence Image Segmentation

目的探讨CT序列图像分割的分割及重建。方法主要结合B样条蛇线算法和模糊边缘增强算法使一些组织器官在CT图像上的二维分割得以实现,同时采用提绘制三维重建分割后的序列图像。临床实践证实,该方法具有良好的效果。程序作为子功能使用,其以Java的医学图像分析系统为基础。结果三维重建的效果对二维分割的精确度极为敏感,有跳变出现在某一幅图像或几幅图像上均会显著影响实体重建。因此,重建效果能够从一定程度上对分割的准确性进行验证。结论运用B样条蛇线算法结合模糊边缘增强算法使分割得以实现,同时运用体绘制方法三维重建分割后的序列图像。实现过程中依据实际改进了这几种算法。图像二维切片、三维重建的结果均显示了良好的效果。

Objective To investigate the segmentation and reconstruction of CT sequence image segmentation.Methods The B-spline snake line algorithm and the fuzzy edge enhancement algorithm were combined to realize the two-dimensional segmentation of some tissues and organs on CT images.At the same time,the sequence images were reconstructed by three-dimensional reconstruction.Clinical practice has confirmed that this method has a good effect.The program is used as a sub-function based on Java’s medical image analysis system.Results The effect of 3D reconstruction is extremely sensitive to the accuracy of 2D segmentation.Jumping on a certain image or several images will significantly affect the volume reconstruction.Therefore,the reconstruction effect can verify the accuracy of the segmentation to some extent.Conclusion Using the B-spline snake line algorithm combined with the fuzzy edge enhancement algorithm to achieve segmentation,the volumetric method is used to reconstruct the segmented sequence image in three dimensions.These algorithms are improved according to the actual implementation process.The results of 2D slice and 3D reconstruction of the image show that good results have been obtained.