Improved watershed transform for medical image segmentation using prior information
Improved watershed transform for medical image segmentation using prior information
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DOI：
10.1109/tmi.2004.824224
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发表时间：
2004-04-01
影响因子：
10.6
通讯作者：
Warfield, SK
中科院分区：
文献类型：
--
作者：
Grau, V;Mewes, AUJ;Warfield, SK
分水岭变换具有有趣的属性，使其可用于许多不同的图像分割应用：它简单直观，可以并行化，并且始终产生图像的完整划分。然而，当应用于医学图像分析时，它具有重要的缺点（过度分割、对噪声敏感、对薄或低信噪比结构的检测不佳）。我们提出了对分水岭变换的改进，可以在其计算中引入先验信息。我们建议通过使用先前的概率计算来引入此信息。此外，我们引入了一种通过使用标记来结合分水岭变换和图谱配准的方法。我们已将新算法应用于两个具有挑战性的应用：膝关节软骨和 MR 图像中的灰质/白质分割。提供了结果的数值验证，证明了医学图像分割算法的强度。
The watershed transform has interesting properties that make it useful for many different image segmentation applications: it is simple and intuitive, can be parallelized, and always produces a complete division of the image. However, when applied to medical image analysis, it has important drawbacks (oversegmentation, sensitivity to noise, poor detection of thin or low signal to noise ratio structures). We present an improvement to the watershed transform that enables the introduction of prior information in its calculation. We propose to introduce this information via the use of a previous probability calculation. Furthermore, we introduce a method to combine the watershed transform and atlas registration, through the use of markers. We have applied our new algorithm to two challenging applications: knee cartilage and gray matter/white matter segmentation in MR images. Numerical validation of the results is provided, demonstrating the strength of the algorithm for medical image segmentation.