Abstract
Medical research is not only expensive but also time-consuming, what can be seen in the queues, and then after the waiting time for the analysis of the effects obtained from tests. In the case of computed tomography examinations, the end result is a series of the described images of the examined object’s shape. The description is made on the careful observation of the results.
In this work, we propose a solution that allows to select images that are suspicious. This type of technique reduces the amount of data that needs to be analyzed and thus reduces the waiting time for the patient. The idea is based on a three-stage data processing. In the first one, key-points are located as features of found elements, in the second, images are constructed containing found areas of images, and in the third, the classifier assesses whether the image should be analyzed in terms of diseases. The method has been described and tested on a large CT dataset, and the results are widely discussed.
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Acknowledgments
Authors acknowledge contribution to this project of the “Diamond Grant 2016” No. 0080/DIA/2016/45 from the Polish Ministry of Science and Higher Education.
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Połap, D., Woźniak, M. (2019). Parallel Processing of Computed Tomography Images. In: Świątek, J., Borzemski, L., Wilimowska, Z. (eds) Information Systems Architecture and Technology: Proceedings of 39th International Conference on Information Systems Architecture and Technology – ISAT 2018. ISAT 2018. Advances in Intelligent Systems and Computing, vol 853. Springer, Cham. https://doi.org/10.1007/978-3-319-99996-8_9
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DOI: https://doi.org/10.1007/978-3-319-99996-8_9
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