Shape and Boundary Similarity Features for Accurate HCC Image Recognition.
Shape and Boundary Similarity Features for Accurate HCC Image Recognition.
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用于准确 HCC 图像识别的形状和边界相似性特征
DOI：
10.1155/2017/3764576
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发表时间：
2017
影响因子：
--
通讯作者：
Li S
中科院分区：
文献类型：
--
作者：
Duan X;Jiang H;Li S
细胞核形态在常规肿瘤病理诊断中具有重要意义，它能直观地提供正常细胞核与异常细胞核之间的信息差异。因此，本文提出了两种新的特征用于正常和肝细胞癌（HCC）的细胞核识别，包括形状和边界相似性。首先，利用中心-增殖分割（CPS）方法获得大小固定的单个核贴片；然后，基于病理学家的人工选择构建核形状库，并利用该库通过Dice、Jaccard、precision和recall系数来衡量核形状的相似性。同时，通过由每个核的一些边界特征点组成的三角形来评估边界相似性。最后，利用常规随机森林（RF）对HCC核识别分类模型进行训练和测试。广泛的交叉验证测试有助于最优特征集的选择，实验对比结果表明，与其他传统特征相比，我们提出的形态学特征更有利于分类。
Nucleus morphology is of great importance in conventional cancer pathological diagnosis, which could provide information difference between normal and abnormal nuclei visually. Therefore, this paper proposes two novel kinds of features for normal and hepatocellular carcinoma (HCC) nucleus recognition, including shape and boundary similarity. First, each individual nucleus patch with the fixed size is obtained using center-proliferation segmentation (CPS) method. Then, nucleus shape library is constructed based on manual selection by pathologists, which is utilized to measure nucleus shape similarity via Dice, Jaccard, precision, and recall coefficients. Meanwhile, boundary similarity is evaluated through triangles composed of some boundary feature points for each nucleus. Finally, the conventional random forest (RF) is used to train and test the classification model for HCC nucleus recognition. Extensive cross-validation tests could facilitate the selection of the optimal feature set and the experiment comparison results demonstrate that our proposed morphological features are more beneficial for classification compared with other traditional characteristics.
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DOI：
10.1109/tgrs.2004.830170
发表时间：
2004-07-01
影响因子：
8.2
作者：
Rellier, G;Descombes, X;Zerubia, J
通讯作者：
Zerubia, J
影响因子：
4.6
作者：
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通讯作者：
Oh, Sukjoong
DOI：
10.1109/34.730558
发表时间：
1998-11-01
影响因子：
23.6
作者：
Itti, L;Koch, C;Niebur, E
通讯作者：
Niebur, E
影响因子：
8
作者：
Huang, Po-Whei;Lai, Yan-Hao
通讯作者：
Lai, Yan-Hao
影响因子：
5.1
作者：
Chen, Xue-wen;Zeng, Xiangyan;van Alphen, Deborah
通讯作者：
van Alphen, Deborah