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

作者：Maglogiannis I^*; Georgakopoulos S V; Tasoulis S K; Plagianakos V P

来源：Information Sciences, 2015, 308: 125-139.

DOI：10.1016/j.ins.2014.10.028

• k-Nearest Neighbors
• Principal Components Analysis
• Microscopy images
• Idiopathic Pulmonary Fibrosis
• Obstructive Nephropathy

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.

• 出版日期2015-7-1