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Cell nucleus segmentation of skin tumor using image processing

机译:皮肤肿瘤使用图像处理细胞核分割

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Automation and quantification of diagnosis of tumor cell images have been studied for these three decades in the field of medical imaging technology. Many techniques of image processing were proposed to solve problems such as nucleus segmentation and classification. But these studies have mainly focused on epithelial tumors. Nonepithelial skin tumors such as dermatofibroma (DF) and dermatofibrosarcoma protuberans (DFSP) have not been enough studied. DF is benign tumorous disease and DFSP is mid-grade malignant tumor. Recently, it is necessary that criterion of classification between DF and DFSP is quantitatively specified. In this paper a system for segmenting cell nuclei of DF and DFSP is proposed. Nuclei regions are objectively segmented and surrounded using edges of strength by the system. Segmentation of arbitrary shaped nuclear regions and weakly stained nuclear region is made. A dynamic thresholding method with combining Laplacian histogram with Ohtsu's method is used for segmentation. Segmentation test was done using real tissue cell images of DF and DFSP to evaluate validity of this system. Shape characteristics such as grade of similarity to circle were also computed from the segmented regions to assure that some differences between DF and DFSP is expressed in its distribution.
机译:已经研究了肿瘤细胞图像诊断的自动化和量化,在医学成像技术领域已经研究了这三十年。提出了许多图像处理技术来解决诸如核细胞分割和分类的问题。但这些研究主要集中在上皮肿瘤上。没有缺乏皮肤肿瘤,如皮肤皮纤维瘤(DF)和Dermatofibrosarcoma蛋白(DFSP)还没有足够的研究。 DF是良性肿瘤疾病,DFSP是中级恶性肿瘤。最近,有必要定量指定DF和DFSP之间分类的标准。本文提出了一种用于DF和DFSP的分段细胞核的系统。核区域客观地分割并使用系统的强度边缘包围。作出了任意形状核区域和弱染色核区域的分割。用ohTSU方法组合Laplacian直方图的动态阈值方法用于分割。使用DF和DFSP的真实组织细胞图像进行分段测试,以评估该系统的有效性。还从分段区域计算出与圆的相似性等级等形状特征,以确保DF和DFSP之间的一些差异在其分布中表示。

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