Quantitative Analysis of Histopathological Features of Precancerous Lesion and Condition Using Image Processing Technique

A. S. Jadhav, S. Banerjee, P. Dutta, R. Paul, M. Pal, P. Banerjee, K. Chaudhuri, J. Chatterjee
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引用次数: 31

Abstract

This paper aims at quantitative analysis of histopathological features of precancerous lesion and condition using image processing technique. The algorithm involves median and low pass filtering, segmentation by adaptive region growing, optimal and local thresholding, morphological operations such as opening and closing of gray scale and binary images and some numerical methods. Differentiation on the basis of type and level of precancerous type or condition is carried out based on image marker, defined as a vector of cancer related features viz. length and curvature of radius of rete-ridges and papillae, population density of cells within epithelium, etc. Implementation of presented algorithms is done in MATLAB. The results support quantitative analysis of pathological condition in respect with progression towards malignancy. This analysis may help in developing automated analysis tool
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利用图像处理技术定量分析癌前病变的组织病理特征及状态
本文旨在利用图像处理技术定量分析癌前病变的组织病理特征和状态。该算法包括中值滤波和低通滤波、自适应区域增长分割、最优阈值分割和局部阈值分割、灰度图像和二值图像的打开和关闭等形态学操作以及一些数值方法。基于癌前病变类型或状况的类型和水平的分化是基于图像标记进行的,图像标记被定义为癌症相关特征的载体,如网脊和乳头半径的长度和曲率,上皮内细胞的密度等。给出的算法在MATLAB中实现。结果支持定量分析病理条件方面的进展向恶性肿瘤。这种分析可能有助于开发自动化分析工具
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