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中文摘要：
在数字医学图像处理中,对于核磁共振图像而言,灰度不均匀性将严重影响算法的性能,因此必须进行偏场的估计以消除这种不均匀性。为此,提出了一种可以同时实现核磁共振图像偏场估计和图像分割的算法。使用最小均方误差准则构建目标函数,利用偏场的光滑特性和局部特性构建约束项来加速算法的收敛速度并提高算法的性能。实验结果表明,该算法能够正确地进行图像分割和偏场校正,同时约束项能够加快算法的收敛速度和提高算法的性能。
英文摘要：
In digital medical image analysis, the intensity inhomogeneity of MR（ magnetic resonance） image can seriously af-fect the performance of the algorithms, and thus the bias field has to be estimated to eliminate inhomogeneity. This paper pro-posed a novel algorithm to achieve the bias field estimation of the MR image, as well as MR image segmentation. The MMSE（minimum mean square error） criterion was applied to build the objective function. A constraint term was constructed basedon the smoothness and the local features of the bias field in order to accelerate convergence and get a better performance. Theexperimental results show that the proposed algorithm segments the image and corrects the bias field precisely. Moreover, theconstraint term can speed up the convergence and improve the performance.
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