基于形态学多尺度修正的脑肿瘤分割

针对脑部核磁共振成像(MRI)图像中因噪声、肿瘤内部灰度不均匀、模糊及边界不连续等造成肿瘤难以准确分割的问题,提出了一种基于形态学多尺度修正的控制标记符分水岭分割方法。该方法在形态学梯度图像基础上,根据不同像素点所在特定邻域内的梯度值自适应确定结构元素的大小;然后,对图像进行形态学多尺度修正,保证修正过程中目标轮廓不发生较大偏移;最后,采用控制标记符的分水岭变换对图像进行分割。实验结果表明,该方法可对脑肿瘤进行较精确的分割。

Brain tumor segmentation based on morphological multi-scale modification

As many methods of brain tumor Magnetic Resonance Imaging (MRI) segmentation are usually driven by such conditions as noise, intensity inhomogeneity within tumor, fuzzy and discontinuous boundaries, it is difficult to segment tumor accurately. To improve the segmentation results, morphological multiscale modification of controlled marker was proposed. Firstly, this method was based on morphological gradient images because the adaptive structure elements were utilized on different pixels in different areas. In addition, modifying gradient image was key to avoid a larger misregistration of target boundaries. Finally, marker-controlled watershed was applied to segment brain tumor. The experimental results show that the method of brain tumors has more accurate segmentation results. Key words：brain tumor; morphological multi-scale modification; watershed transform