A software tool for the automatic detection and quantification of fibrotic tissues in microscopy images

被引:4
|
作者
Maglogiannis, I. [1 ]
Georgakopoulos, S. V. [2 ]
Tasoulis, S. K. [3 ]
Plagianakos, V. P. [2 ]
机构
[1] Univ Piraeus, Dept Digital Syst, Grigoriou Lampraki 126, Piraeus 18532, Greece
[2] Univ Thessaly, Dept Comp Sci & Biomed Informat, Lamia 35100, Greece
[3] Univ Helsinki, Dept Comp Sci, Helsinki Inst Informat Technol, FI-00014 Helsinki, Finland
基金
芬兰科学院;
关键词
k-Nearest Neighbors; Principal Components Analysis; Microscopy images; Idiopathic Pulmonary Fibrosis; Obstructive Nephropathy; LIVER FIBROSIS; SEMIQUANTITATIVE INDEXES; RECOGNITION; VALIDATION; DESIGN;
D O I
10.1016/j.ins.2014.10.028
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The high volume of pathological microscopy images deforming tissues make the fast quantification and detection of the corrupted regions extremely difficult. To tackle this problem, we present in this paper an automated computer based tool that allows the easy selection of training regions for the various type of pathologies and adopts dimensionality reduction and classification methods for detecting and quantifying the infected areas. The output of the proposed tool is a classification result superimposed on original images, along with an overall index indicating the severity of the pathology. The experimental results are promising, since the tool exhibits high classification accuracy and the calculated index is compatible with expert physician's estimation of the degree of pathology. (C) 2014 Elsevier Inc. All rights reserved.
引用
收藏
页码:125 / 139
页数:15
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