基于3D區(qū)域增長法和改進的凸包算法相結合的全肺分割方法

代雙鳳; 呂科; 翟銳; 董繼陽

doi:10.11999/JEIT151365

基于3D區(qū)域增長法和改進的凸包算法相結合的全肺分割方法

doi: 10.11999/JEIT151365 cstr: 32379.14.JEIT151365

基金項目:

國家自然科學基金(U1301251, 61271435)，北京市自然科學基金(4141003)

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- 被引次數: 0
出版歷程
- 收稿日期: 2015-12-03
- 修回日期: 2016-05-10
- 刊出日期: 2016-09-19

Lung Segmentation Method Based on 3D Region Growing Method and Improved Convex Hull Algorithm

Funds:

The National Natural Science Foundation of China (U1301251, 61271435), Beijing Natural Science Foundation (4141003)

摘要

摘要: 肺實質分割結果的準確性在實際臨床應用中具有非常重要的意義。但由于肺結節(jié)的位置、大小、形狀的不規(guī)則性，肺部病變的多樣性，以及人體胸部解剖結構的明顯差異等，使得各類分割方法不能統(tǒng)一地適用于所有的胸部CT圖像，所以對于肺實質分割方法的研究仍具有很大的挑戰(zhàn)。該文在國內外研究分析的基礎上提出基于3D區(qū)域增長法與改進的凸包修補算法相結合的全肺分割方法。在3D區(qū)域增長法的粗分割基礎上，對分割的結果進行細化工作，通過連通域標記法與形態(tài)學方法相結合去除氣管和主支氣管，得到初步的肺實質掩膜，最后應用改進的凸包算法對肺部輪廓進行修補平滑，最終得到肺部分割結果。通過與凸包算法及滾球法相對比，證明該文所提改進的凸包算法能夠有效地修補肺部輪廓凹陷，修補后的結果分割精度較高。
- 肺部分割 /
- 3D區(qū)域增長法 /
- 凸包算法 /
- 區(qū)域連通分析
Abstract: The accuracy of lung segmented results is important in actual clinical application. However, all kinds of segmentation methods can not be uniform for all the chest CT (Computed Tomography) images because of the irregularities and diversity of lung disease, as well as significant differences in the anatomy of the human chest. Lung parenchyma segmentation studies still have a great challenge. Based on the analysis of domestic and international research, a new lung segmentation method is presented by combining with 3D region growing method and improved convex hull patching algorithm. Firstly, the 3D region growing method is adopted for the rough segmentation of lung CT images. Then the refining work is done to the segmented results. The connected domain labeling and morphological methods are used to remove the trachea and main bronchi to get the pulmonary parenchyma mask. The improved convex hull algorithm is presented to repair and smooth the concavities of lung contour. Finally, the segmented results can be gotten. The improved convex hull algorithm can repair the concavities of lung contour effectively in comparison with the convex hull algorithm and the rolling ball method, and the segmentation precision of results is very high after repairing.
- Lung segmentation /
- 3D region growing method /
- Convex hull algorithm /
- Connected domain processing

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