Three-dimensional Texture Analysis of Renal Cell Carcinoma Cell Nuclei for Computerized Automatic Grading
| Autor: | Hyun-Ju Choi, Heung-Kook Choi, Tae-Yun Kim, Hae-Gil Hwang |
|---|---|
| Rok vydání: | 2009 |
| Předmět: |
Computer science
Confocal Medicine (miscellaneous) Health Informatics Sensitivity and Specificity Digital image Imaging Three-Dimensional Health Information Management Image Interpretation Computer-Assisted Microscopy Humans Computer vision Carcinoma Renal Cell Grading (tumors) Principal Component Analysis Microscopy Confocal business.industry Pattern recognition Linear discriminant analysis Chromatin Kidney Neoplasms Principal component analysis Artificial intelligence business Cytometry Texture mapping Information Systems |
| Zdroj: | Journal of Medical Systems. 34:709-716 |
| ISSN: | 1573-689X 0148-5598 |
| DOI: | 10.1007/s10916-009-9285-6 |
| Popis: | The extraction of important features in cancer cell image analysis is a key process in grading renal cell carcinoma. In this study, we analyzed the three-dimensional chromatin texture of cell nuclei based on digital image cytometry. Individual images of 2,423 cell nuclei were extracted from 80 renal cell carcinomas (RCCs) using confocal laser scanning microscopy (CLSM). First, we applied the 3D texture mapping method to render the volume of entire tissue sections. Then, we determined the chromatin texture quantitatively by calculating 3D gray level co-occurrence matrices and 3D run length matrices. Finally, to demonstrate the suitability of 3D texture features for classification, we performed a discriminant analysis. In addition, we conducted a principal component analysis to obtain optimized texture features. Automatic grading of cell nuclei using 3D texture features had an accuracy of 78.30%. Combining 3D textural and 3D morphological features improved the accuracy to 82.19%. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink