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Grid-Enabled , High-performance Microscopy Image Analysis

Biomedical images are intrinsically complex with each domain and modality often requiring specialized knowledge to accurately render diagnosis and plan treatment. Having a general software framework, which provides access to high-performance resources, can serve to facilitate high-throughput investigations of micro-scale features as well as algorithm design, development and evaluation. In this paper we describe the requirements and challenges of supporting microscopy analyses of large datasets of high-resolution biomedical images. We present high-performance computing approaches for storage and retrieval of image data, image processing, and management of analysis results for additional explorations. We describe the implementation of a Grid-enabled analysis component for quantitative investigation of tissue microarrays and present empirical performance results.