| Literature DB >> 18982583 |
Thomas J Fuchs1, Peter J Wild, Holger Moch, Joachim M Buhmann.
Abstract
Renal cell carcinoma (RCC) can be diagnosed by histological tissue analysis where exact counts of cancerous cell nuclei are required. We propose a completely automated image analysis pipeline to predict the survival of RCC patients based on the analysis of immunohistochemical staining of MIB-1 on tissue microarrays. A random forest classifier detects cell nuclei of cancerous cells and predicts their staining. The classifier training is achieved by expert annotations of 2300 nuclei gathered from tissues of 9 different RCC patients. The application to a test set of 133 patients clearly demonstrates that our computational pathology analysis matches the prognostic performance of expert pathologists.Entities:
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Year: 2008 PMID： 18982583 DOI： 10.1007/978-3-540-85990-1_1
Source DB: PubMed Journal: Med Image Comput Comput Assist Interv