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Computational pathology: Challenges and promises for tissue analysis

Fuchs, Thomas J. and Buhmann, Joachim M. (2011) Computational pathology: Challenges and promises for tissue analysis. Computerized Medical Imaging and Graphics, 35 (7-8). pp. 515-530. ISSN 0895-6111. https://resolver.caltech.edu/CaltechAUTHORS:20111101-083725218

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Abstract

The histological assessment of human tissue has emerged as the key challenge for detection and treatment of cancer. A plethora of different data sources ranging from tissue microarray data to gene expression, proteomics or metabolomics data provide a detailed overview of the health status of a patient. Medical doctors need to assess these information sources and they rely on data driven automatic analysis tools. Methods for classification, grouping and segmentation of heterogeneous data sources as well as regression of noisy dependencies and estimation of survival probabilities enter the processing workflow of a pathology diagnosis system at various stages. This paper reports on state-of-the-art of the design and effectiveness of computational pathology workflows and it discusses future research directions in this emergent field of medical informatics and diagnostic machine learning.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1016/j.compmedimag.2011.02.006DOIUNSPECIFIED
http://www.sciencedirect.com/science/article/pii/S0895611111000383PublisherUNSPECIFIED
Additional Information:© 2011 Elsevier Ltd. Received 29 June 2010; revised 21 January 2011; Accepted 23 February 2011. Available online 9 April 2011. The authors wish to thank Holger Moch and Peter Schraml for their help in conducting the RCC TMA project, Peter Wild and Peter Bode for annotating the medical data and Monika Bieri and Norbert Wey for scanning and tiling the TMA slides. Special thanks also to Volker Roth and Sudhir Raman for valuable discussions. We also acknowledge financial support from the FET program within the EU FP7, under the SIMBAD project (Contract 213250).
Funders:
Funding AgencyGrant Number
European Union FP7 SIMBAD Project213250
Subject Keywords:Computational pathology; Machine learning; Medical imaging; Survival statistics; Cancer research; Whole slide imaging
Issue or Number:7-8
Record Number:CaltechAUTHORS:20111101-083725218
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20111101-083725218
Official Citation:Thomas J. Fuchs, Joachim M. Buhmann, Computational pathology: Challenges and promises for tissue analysis, Computerized Medical Imaging and Graphics, Volume 35, Issues 7-8, October-December 2011, Pages 515-530, ISSN 0895-6111, 10.1016/j.compmedimag.2011.02.006. (http://www.sciencedirect.com/science/article/pii/S0895611111000383)
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:27541
Collection:CaltechAUTHORS
Deposited By: Ruth Sustaita
Deposited On:01 Nov 2011 15:55
Last Modified:03 Oct 2019 03:24

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