Background and objective

Accurate segmentation of solitary pulmonary nodule of digital radiography image is essential for lesion appearance measurement and medical follow-up. However, the imaging characteristics of digital radiography, the inhomogeneity and fuzzy contours of nodules often lead to poor performances. This work aims to develop a segmentation framework that satisfies the requirements of accurate segmentation.

Methods

In this work, an interactive segmentation method which combined the enhanced total-variance pyramid and improved Grab cut was proposed to improve the performance of nodule segmentation. The edge-preserving multi-resolution pyramid structure did the rough segmentation on low resolution images, which provided contour nearby curves to initial the following accuracy segmentation and shortened the time of energy decreasing. With the multiscale information being incorporated to optimize the edge term and improve the appearance model, a novel Gibbs energy functional was constructed to extract the nodule in a proper scale. By introducing the multiscale processing and optimizing the energy terms, the proposed method could overcome the inhomogeneity and fuzzy contours.

Results

For evaluation of the nodule segmentation, quantitative metrics such as precision, intersection over union, and dice similarity coefficient were introduced and compared in the experimental part. The proposed solitary pulmonary nodule segmentation method produced the results with mean values of precision 0.957, dice similarity coefficient 0.933, and intersection over union 0.891, respectively. And the corresponding standard deviation values were 0.041, 0.047, and 0.045.

Conclusions

From the quantitative assessment and comparison in the experiments, the proposed method achieved a competitive performance in accuracy and stability, even in the cases with low contrast and fuzzy contours.

中文翻译：

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基于金字塔和改进抓割的孤立性肺结节分割

背景和目标

数字X线照片的孤立肺结节的准确分割对于病变外观测量和医学随访至关重要。然而，数字射线照相的成像特性，结节的不均匀性和模糊轮廓经常导致较差的性能。这项工作旨在开发一种满足准确细分要求的细分框架。

方法

在这项工作中，提出了一种交互式分割方法，该方法结合了增强的总方差金字塔和改进的Grab割，以提高结节分割的性能。保留边缘的多分辨率金字塔结构在低分辨率图像上进行了粗略的分割，为初始的后续精度分割提供了轮廓附近的曲线，并缩短了能量降低的时间。通过合并多尺度信息以优化边缘项并改善外观模型，构建了一种新型的吉布斯能量泛函，以适当的尺度提取结节。通过引入多尺度处理和优化能量项，该方法可以克服不均匀性和模糊轮廓。

结果

为了评估结节分割，在实验部分引入并比较了定量指标，例如精度，交集交点和骰子相似系数。所提出的孤立肺结节分割方法产生的结果的平均值分别为精度0.957，骰子相似系数0.933和交集交会0.891。相应的标准偏差值为0.041、0.047和0.045。

结论

通过实验中的定量评估和比较，即使在对比度低且轮廓模糊的情况下，该方法仍能在准确性和稳定性上达到竞争优势。