A novel texture descriptor for detection of glandular structures in colon histology images
A novel texture descriptor for detection of glandular structures in colon histology images
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DOI：
10.1117/12.2082010
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发表时间：
2015-03
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影响因子：
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通讯作者：
K. Sirinukunwattana;D. Snead;N. Rajpoot
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文献类型：
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作者：
K. Sirinukunwattana;D. Snead;N. Rajpoot
对大多数组织病理学图像进行大多数分析之前的第一步是检测感兴趣区域。在这项工作中，我们提出了一种基于超像素的方法，用于结肠组织学图像中的腺体结构检测。首先将图像分割成超像素，并限制腺体边界的存在。然后从每个超像素中提取纹理和颜色信息，以计算该超像素属于腺体区域的概率，从而产生腺体概率图。此外，我们提出了一种从散射系数的区域协方差矩阵导出的新颖的纹理描述符。我们的方法在结肠组织样本中腺体结构的检测方面显示出令人鼓舞的结果。
The first step prior to most analyses on most histopathology images is the detection of area of interest. In this work, we present a superpixel-based approach for glandular structure detection in colon histology images. An image is first segmented into superpixels with the constraint on the presence of glandular boundaries. Texture and color information is then extracted from each superpixel to calculate the probability of that superpixel belonging to glandular regions, resulting in a glandular probability map. In addition, we present a novel texture descriptor derived from a region covariance matrix of scattering coefficients. Our approach shows encouraging results for the detection of glandular structures in colon tissue samples.