Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
506008 | Computers in Biology and Medicine | 2007 | 8 Pages |
Abstract
This study attempted to develop a method for 3D visualization and quantitative analysis of cell nuclei for renal cell carcinoma (RCC) grading and evaluated the feasibility of such quantitative analysis. We compared the correct classification rate (CCR) for each of the classifiers based on the 2D features of cell nuclei (diameter, area, perimeter, and circularity) and the 3D features of cell nuclei (volume, surface area, and spherical shape factor). The results showed that the classifier using the 3D features provided better results for grading. Our method could overcome the limitations inherent in 2D analysis and could improve the accuracy and reproducibility of quantification of cell nuclei.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Hyun-Ju Choi, Heung-Kook Choi,