High Performance Spatial Query Processing for Large Scale Scientific Data
Analyzing and querying large volumes of spatially derived data from scientific experiments has posed major challenges in the past decade. For example, the systematic analysis of imaged pathology specimens result in rich spatially derived information with "GIS" characteristics at cellular and sub-cellular scales, with nearly a million derived markups and hundred million features per image. This provides critical information for evaluation of experimental results, support of biomedical studies and pathology image based diagnosis. However, the vast amount of spatially oriented morphological information poses major challenges for analytical medical imaging.