Abstract
In previous papers we presented a computer system to detect erosions and osteophytes from hand radiographs (the most common symptoms of rheumatic diseases) based on the shape analysis of the joint surfaces borders. Such borders are obtained automatically using algorithms which were also proposed in our previous articles. In this paper, we consider a new approach which analyzes patches located at the joint surfaces borders in order to determine which of them correspond to the lesions. Vectors of features which are used to classify patches are calculated by applying Schmid filter with various frequencies and scales. Additional features are obtained using inpainting. Vectors are analyzed based on Gaussian mixture model calculated with expectation maximization algorithm. The accuracy is measured with area under curve of the receiver-operating characteristic. The conducted experiments proved that, the shape approach described in our previous work can be improved by applying Schmid filter and the inpainting approach in the parsing stage, especially, in case of the lower MCP and upper PIP surfaces for which classification still remains inaccurate.
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Zieliński, B., Skomorowski, M. (2016). Schmid Filter and Inpainting in Computer-Aided Erosions and Osteophytes Detection Based on Hand Radiographs. In: Burduk, R., Jackowski, K., Kurzyński, M., Woźniak, M., Żołnierek, A. (eds) Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015. Advances in Intelligent Systems and Computing, vol 403. Springer, Cham. https://doi.org/10.1007/978-3-319-26227-7_48
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DOI: https://doi.org/10.1007/978-3-319-26227-7_48
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