@inproceedings{2a4d0bfaaf364042ab7bc89fbb68dd78,
title = "Computational pathology analysis of tissue microarrays predicts survival of renal clear cell carcinoma patients",
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.",
author = "Fuchs, {Thomas J.} and Wild, {Peter J.} and Holger Moch and Buhmann, {Joachim M.}",
year = "2008",
doi = "10.1007/978-3-540-85990-1_1",
language = "English",
isbn = "3540859896",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
number = "PART 2",
pages = "1--8",
booktitle = "Medical Image Computing and Computer-Assisted Intervention - MICCAI 2008 - 11th International Conference, Proceedings",
address = "Germany",
edition = "PART 2",
note = "11th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2008 ; Conference date: 06-09-2008 Through 10-09-2008",
}