Efficient similarity search on 3D bounding box annotations

Hans-Peter Kriegel; Marisa Petri; Matthias Schubert; Michael Shekelyan; Michael Stockerl

doi:10.1117/12.911292

16 February 2012 Efficient similarity search on 3D bounding box annotations

Hans-Peter Kriegel, Marisa Petri, Matthias Schubert, Michael Shekelyan, Michael Stockerl

Proceedings Volume 8319, Medical Imaging 2012: Advanced PACS-based Imaging Informatics and Therapeutic Applications; 83190B (2012) https://doi.org/10.1117/12.911292
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

Searching for similar image regions in medical databases yields valuable information for diagnosis. However, most of the current approaches are restricted to special cases or they are only available for rather small data stores. In this paper, we propose a fast query pipeline for 3D similarity queries on large databases of computed tomography (CT) scans consisting of minimum bounding box annotations. As these box annotations also contain background information which is not part of the item that was actually annotated, we employ approximate segmentation approaches for distinguishing between within-object texture and background texture in order to correctly describe the annotated objects. Our method allows a compact form of object description. In our framework, we exploit this advantage for enabling very fast query times. We have validated our method on data sets of 111 and 1293 bounding box lesion annotations within the liver and other organs. Our experiments show a significant performance improvement over previous approaches in both runtime and precision.

Citation Download Citation

Hans-Peter Kriegel, Marisa Petri, Matthias Schubert, Michael Shekelyan, and Michael Stockerl "Efficient similarity search on 3D bounding box annotations", Proc. SPIE 8319, Medical Imaging 2012: Advanced PACS-based Imaging Informatics and Therapeutic Applications, 83190B (16 February 2012); https://doi.org/10.1117/12.911292

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