计算机科学 ›› 2013, Vol. 40 ›› Issue (1): 269-272.

• 图形图像与模式识别 • 上一篇    下一篇

医学三维影像体数据闭值分割方法

朱代辉,林时苗,杨育彬   

  1. (南京大学计算机软件新技术国家重点实验室 南京210093)
  • 出版日期:2018-11-16 发布日期:2018-11-16

Threshold-based Segmentation for 3D Medical Volumetric Images

  • Online:2018-11-16 Published:2018-11-16

摘要: 建立医学三维体数据阂值分割描述模型,把()S I'U图像分割算法和梯度算子图像分割算法的思想应用于三 维体数据,提出并实现了两种医学三维体数据阂值分割算法,并通过实验证明这两种算法获得了较好的分割效果。为 进一步对体数据阂值分割算法的性能进行量化评价,定义了两个量化指标:分割准确度和分割平衡度,并通过实验给 出了上述两种体数据阂值分割算法的性能评价指标。在给定体数据和标准分割的前提下,OSTU算法比梯度算子算 法能取得更好的阂值分割效果。

关键词: 三维医学图像,体数据,医学图像处理

Abstract: This paper presented a threshold-based segmentation framework for 3D medical volumetric images, in which two classical image segmentation algorithms, OSTU and Gradient based Segmentation, were re-designed and optimized to be suitable for 3D volumetric images. In order to evaluate the framework's performance, we defined two novel ctuanti- tative performance indicators: Segmentation Accuracy and Segmentation Balance, and use them to evaluate and analyze their performances. Experimental results show that both of the proposed segmentation algorithms can yield satisfied segmentation results for 3D medical volumetric images, and OShU segmentation achieves better performance than Gra- dicnt-based segmentation.

Key words: 3D medical image segmentation, Volumetric data, Medical image processing

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