Yang Song
ABSTRACT
Content-based medical image retrieval is likely becoming an important tool to provide valuable information to assist physician to make critical diagnosis decisions. While most existing works perform the retrieval based on low-level visual features, the pathological spatial context, which is critical for analysis of the disease characteristics, has been less studied. We thus aim to effectively extract and represent the spatial context of pathological tissues, and design a novel hierarchical spatial matching (HSM) method based on the spatial pyramid matching. Our method is able to (1) handle the translation variations of the main pathological object; (2) describe the spatial information surrounding the pathological object in an adaptive scale; and (3) compute image similarities with an optimally weighted distance function. The proposed method shows better retrieval performance comparing to the other widely used techniques.
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Index Terms
- Hierarchical spatial matching for medical image retrieval
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