Supervoxel Graph Cuts: An Effective Method for GGO Candidate Regions Extraction on CT Images

Lu Huimin; Kondo Masashi; Li Yujie; Tan JooKooi; Kim Hyoungseop; Murakami Seiichi; Aoki Takatoshi; Kido Shoji

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Supervoxel Graph Cuts: An Effective Method for GGO Candidate Regions Extraction on CT Images

机译：Supervoorel图表切割：在CT图像上提取GGO候选区域的有效方法

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In this article, a method to reduce artifacts on temporal difference images is introduced. The proposed method uses a nonrigid registration method for ground glass opacification (GGO), which is light in concentration and difficult to detect early. In this method, global matching, local matching, and three-dimensional (3D) elastic matching are performed on the current and previous images, and an initial temporal subtraction image is generated. After that, we use an Iris filter, which is the gradient vector concentration degree filter, to determine the initial GGO candidate regions and use supervoxel and graph cuts to segment region of interest in the 3D images. For each extracted region, a support vector machine is used to reduce the oversegmentation. The voxel matching is applied to generate the final temporal difference image, emphasizing the GGO regions while reducing the artifact.

机译：在本文中，引入了减少时间差异图像上的伪影的方法。该方法使用用于磨削玻璃透明度（GGO）的非脂肪配准法，其浓度轻，难以早发检测。在该方法中，对电流和先前图像执行全局匹配，本地匹配和三维（3D）弹性匹配，并且生成初始时间减法图像。之后，我们使用IRIS滤波器，该虹膜滤波器是梯度向量浓度滤波器，以确定初始GGO候选区域，并使用SupervoOxel和图表切割到3D图像中的段景点区域。对于每个提取区域，使用支撑载体机用于减少过度的解除。应用体素匹配来产生最终的时间差异图像，在减少工件的同时强调GGO区域。

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来源
《Consumer Electronics Magazine, IEEE》 |2020年第1期|61-66|共6页
作者
Lu Huimin; Kondo Masashi; Li Yujie; Tan JooKooi; Kim Hyoungseop; Murakami Seiichi; Aoki Takatoshi; Kido Shoji;
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作者单位

Kyushu Inst Technol Kitakyushu Fukuoka Japan;

Kyushu Inst Technol Kitakyushu Fukuoka Japan;

Fukuoka Univ Fukuoka Fukuoka Japan;

Kyushu Inst Technol Dept Mech & Control Engn Kitakyushu Fukuoka Japan;

Kyushu Inst Technol Dept Control Engn Kitakyushu Fukuoka Japan;

Kyushu Inst Technol Dept Mech & Control Engn Kitakyushu Fukuoka Japan;

Univ Occupat & Environm Hlth Dept Radiol Kitakyushu Fukuoka Japan;

Grad Sch Sci & Technol Innovat Suita Osaka Japan;

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正文语种 eng
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Computed tomography; Cancer; Image registration; Three-dimensional displays; Lung; Lesions;

机译：计算断层扫描;癌症;图像配准;三维显示器;肺;病变;

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专利

1. Supervoxel Graph Cuts: An Effective Method for GGO Candidate Regions Extraction on CT Images [J] . Progress in Artificial Intelligence . 2020,第1期

机译：超级环图削减：对GGO候选区域提取CT图像的有效方法
2. Extraction of GGO Candidate Regions on Thoracic CT Images using SuperVoxel-Based Graph Cuts for Healthcare Systems [J] . Lu Huimin, Kondo Masashi, Li Yujie, Mobile networks & applications . 2018,第6期

机译：使用基于SuperVoxel的图形切割在胸部CT图像上提取GGO候选区域，用于医疗保健系统
3. An effective edge extraction method using improved local binary pattern for blurry digital radiography images [J] . Bi Bi, Li Zeng, Kuan Shen, NDT & E international . 2013,第JANa期

机译：使用改进的局部二值模式处理模糊数字放射线图像的有效边缘提取方法
4. 3D GGO candidate extraction in lung CT images using multilevel thresholding on supervoxels [C] . Shan Huang, Xiabi Liu, Guanghui Han, SPIE Medical Imaging Conference . 2018

机译：在超级体素上使用多级阈值提取肺部CT图像中的3D GGO候选对象
5. Hybrid method: Algebraic/Inverse Radon Transform for region of interest reconstruction of computed tomography images [D] . Barrera Cruz, Marco Antonio 2009

机译：混合方法：代数/逆Rad变换，用于重建计算机断层扫描图像的感兴趣区域
6. Automatic Liver Segmentation on Volumetric CT Images Using Supervoxel-Based Graph Cuts [O] . Weiwei Wu, Zhuhuang Zhou, Shuicai Wu, 2016

机译：使用基于Supervoxel的图割对体积CT图像进行自动肝分割
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Supervoxel Graph Cuts: An Effective Method for GGO Candidate Regions Extraction on CT Images

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