在图像引导下的前列腺磁共振图像分割的介入诊断与治疗具有重要意义.本文对距离正则化水平集演化（DRLSE）方法进行了改进并用于前列腺磁共振图像分割.前列腺磁共振图像中靠近膀胱一侧边界较为模糊，靠近尿道一侧及左右两侧边界较为清晰，仅用传统的梯度信息指示函数无法达到理想分割结果.本研究分别采用两个指示函数控制边界清晰段及模糊段的演化，以达到准确分割的目的.此外，还在外部能量函数中增加了能量牵制项，避免演化在虚假边界停止，驱使水平集向灰度波动较大的区域移动，并能在模糊边界停止演化.实验表明利用本方法进行前列腺磁共振图像分割的效果较好；Dice相似性系数（DSC）均值达到96%，接近专家手动分割结果.
Segmentation of prostate magnetic resonance images is of great significance in the interventional diagnosis and treatment of prostate diseases. In this work, the conventional distance regularized level set evolution (DRLSE) model is improved and applied to prostate segmentation. In magnetic resonance image, the prostate boundary near the bladder is often blurred, while that near the urethra is clear, resulting in a poor performance for the traditional gradient information indicator function. In this study, two indicator functions were used to control the evolution of boundary in the clear segment and blurred segment, respectively, to achieve better segmentation. In addition, an energy check term was added to the external energy function to prevent evolution from stopping at a false boundary. This modification could drive the level set to move to regions with large gray level fluctuation and stop evolution at a blurred boundary. Experimental results demonstrated that the performance of prostate segmentation was satisfactory, judging from the Dice similarity coefficient (DSC) which reached an average of 96%.
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