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Computational and Mathematical Methods in Medicine
Volume 2014, Article ID 536217, 12 pages
Research Article

3D Texture Analysis in Renal Cell Carcinoma Tissue Image Grading

1Department of Computer Engineering, Inje University, Injero 197, UHRC, Gimhae, Gyeongnam 621-749, Republic of Korea
2Department of Pathology, Yonsei University, Seoul 120-749, Republic of Korea
3Department of Anatomy, Gachon University, Incheon 406-799, Republic of Korea
4Centre for Image Analysis, Uppsala University, 75105 Uppsala, Sweden

Received 1 June 2014; Revised 31 August 2014; Accepted 3 September 2014; Published 9 October 2014

Academic Editor: Po-Hsiang Tsui

Copyright © 2014 Tae-Yun Kim et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


One of the most significant processes in cancer cell and tissue image analysis is the efficient extraction of features for grading purposes. This research applied two types of three-dimensional texture analysis methods to the extraction of feature values from renal cell carcinoma tissue images, and then evaluated the validity of the methods statistically through grade classification. First, we used a confocal laser scanning microscope to obtain image slices of four grades of renal cell carcinoma, which were then reconstructed into 3D volumes. Next, we extracted quantitative values using a 3D gray level cooccurrence matrix (GLCM) and a 3D wavelet based on two types of basis functions. To evaluate their validity, we predefined 6 different statistical classifiers and applied these to the extracted feature sets. In the grade classification results, 3D Haar wavelet texture features combined with principal component analysis showed the best discrimination results. Classification using 3D wavelet texture features was significantly better than 3D GLCM, suggesting that the former has potential for use in a computer-based grading system.