Bone marrow cavity segmentation using graph-cuts with wavelet-based texture feature
Bone marrow cavity segmentation using graph-cuts with wavelet-based texture feature
复制标题
使用基于小波纹理特征的图形切割进行骨髓腔分割
DOI：
10.1142/s0219720017400042
复制
发表时间：
2017
影响因子：
1
通讯作者：
et.al
中科院分区：
文献类型：
--
作者：
Shigeta Hironori;Mashita Tomohiro;Junichi Kikuta;Shigeto Seno;et.al
新兴的生物成像技术使我们能够捕捉各种动态细胞活动。随着大量的数据被获得这些天，它变得不切实际的手动处理大量的图像，自动分析方法是必需的。自动图像分割的问题之一是图像拍摄条件是可变的。因此，通常，根据每个图像需要许多手动输入。针对骨髓腔（BMC）与骨重建、骨质疏松等疾病的发生机制密切相关的特点，提出了一种基于小波变换和支持向量机的骨髓腔图像分割方法。由于纹理分析不考虑空间连续性，我们还将纹理模式分类的结果集成到基于图割的图像分割方法中。我们的方法是适用于一个特定的帧中的图像序列中的荧光材料的条件是可变的。在实验中，我们评估了我们的方法与九种类型的母小波和几组尺度参数。所提出的方法与图形切割和纹理模式分类执行良好，无需用户手动输入。
Emerging bioimaging technologies enable us to capture various dynamic cellular activities. As large amounts of data are obtained these days and it is becoming unrealistic to manually process massive number of images, automatic analysis methods are required. One of the issues for automatic image segmentation is that image-taking conditions are variable. Thus, commonly, many manual inputs are required according to each image. In this paper, we propose a bone marrow cavity (BMC) segmentation method for bone images as BMC is considered to be related to the mechanism of bone remodeling, osteoporosis, and so on. To reduce manual inputs to segment BMC, we classified the texture pattern using wavelet transformation and support vector machine. We also integrated the result of texture pattern classification into the graph-cuts-based image segmentation method because texture analysis does not consider spatial continuity. Our method is applicable to a particular frame in an image sequence in which the condition of fluorescent material is variable. In the experiment, we evaluated our method with nine types of mother wavelets and several sets of scale parameters. The proposed method with graph-cuts and texture pattern classification performs well without manual inputs by a user.
用于量化骨组织屏障渗透的图切图像分割方法
DOI：
10.1109/i3a.2014.22
发表时间：
2014
期刊：
2014 1st Workshop on Pattern Recognition Techniques for Indirect Immunofluorescence Images
影响因子：
--
作者：
Hironori Shigeta;T. Mashita;Takeshi Kaneko;J. Kikuta;S. Seno;H. Takemura;H. Matsuda;M. Ishii
通讯作者：
M. Ishii
使用受限 SMC 簇通过双光子显微镜成像追踪 T 细胞和 B 细胞
影响因子：
1.9
作者：
D. Olivieri;J. Faro;Iván Gómez;C. Tadokoro
通讯作者：
C. Tadokoro