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Structural Analysis of Histological Images to Aid Diagnosis of Cervical Cancer

机译:组织学图像结构分析对宫颈癌的诊断价值

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The use of computational techniques in the processing of histopathological images allows the study of the structural organization of tissues and their pathological changes. The overall objective of this work includes the proposal, the implementation and the evaluation of a methodology for the analysis of cervical intraepithelial neoplasia (CIN) from histopathological images. For this pourpose, a pipeline of morphological operators were implemented for the segmentation of cell nuclei and the Delaunay Triangulation were used in order to represent the tissue architecture. Also, clustering algorithms and graph morphology were used to automatically obtain the boundary between the histological layers of the epithelial tissue. Similarity criteria and adjacency relations between the triangles of the network were explored. The proposed method was evaluated concerning the detection of the presence of lesions in the tissue as well as the their malignancy grading.
机译:在组织病理学图像的处理中使用计算技术可以研究组织的结构组织及其病理变化。这项工作的总体目标包括从组织病理学图像分析宫颈上皮内瘤样变(CIN)的方法的提议,实施和评估。为此,实施了一系列的形态学算子用于细胞核的分割,并使用Delaunay三角剖分法来表示组织结构。同样,使用聚类算法和图形态来自动获得上皮组织的组织学层之间的边界。探索了网络三角形之间的相似性准则和邻接关系。对提议的方法进行了评估,涉及检测组织中病变的存在及其恶性程度。

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