Abstract
In this study we present an efficient image categorization system for medical image databases utilizing a local patch representation based on both content and location. The system discriminates between healthy and pathological cases and indicates the subregion in the image that is automatically found to be most relevant for the decision. We show an application to pathology-level categorization of chest x-ray data, the most popular examination in radiology. Experimental results are provided on chest radiographs taken from routine hospital examinations. © 2011 Springer-Verlag.
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CITATION STYLE
Avni, U., Greenspan, H., & Goldberger, J. (2011). X-ray categorization and spatial localization of chest pathologies. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6893 LNCS, pp. 199–206). https://doi.org/10.1007/978-3-642-23626-6_25
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