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2001

Image-Feature Extraction for Protein Crystallization: Integrating Image Analysis and Case-Based Reasoning

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Image-Feature Extraction for Protein Crystallization: Integrating Image Analysis and Case-Based Reasoning
This paper describes issues related to integrating image analysis techniques into case-based reasoning. Although the approach is generic, a high-throughput protein crystallization problem is used as an example. Our solution to the crystallization problem is to store outcomes of experiments as images, extract important image features, and use them to automatically recognize different crystallization outcomes. Subsequently, we use the outcomes of image classification to perform case-based planning of crystallization experiments for new proteins. Knowledge-discovery techniques are used to extract general principles for crystallization. Such principles are applicable to the adaptation phase of case-based reasoning. The motivation for automated image-feature extraction is twofold: (1) the human interpretation/analysis of image content is subjective, and (2) many problem domains require reasoning with large databases of uninterpreted images. In this paper we present the design and implement...
Igor Jurisica, Phil Rogers, Janice I. Glasgow, Suz
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2001
Where IAAI
Authors Igor Jurisica, Phil Rogers, Janice I. Glasgow, Suzanne Fortier, Joseph R. Luft, Melissa A. Bianca, Robert J. Collins, George T. DeTitta
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