Abstract
The article presents an innovative method of kidney recognition in computed tomography (CT) images. Kidney cancer is one of the most common causes of death. Over 300,000 people die per year from this disease. A fast and correct diagnosis of neoplastic lesions in computed tomography images allows to choose the proper method of treatment. This article presents innovative and unique methods of kidney recognition in CT images. The proposed methods are based on morphological operations, shape analysis, geometrical coefficients calculations as well as the directional operation of flood fill with automatic selection of the stop criterion. The article presents also an innovative method of closing the boundary of an unrecognized kidney. Application of fast and effective algorithms for an automatic kidney shape recognition allows to make a 3D reconstruction of the kidney model. The use of algorithms to improve visualization of CT scans allows more accurate diagnosis by specialists. The system for supporting kidney cancer diagnosis presented in the article has been tested to assess the quality of kidney shape recognition. The recognition results of the shape of the kidney by the automatic system are comparable to the results obtained by a human expert and the accuracy of the diagnosis is at the level of 86%. Despite the difficult task, it was possible to obtain satisfactory results of the kidney shape recognition.
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Acknowledgment
This work has been supported by the National Science Centre (2016/23/B/ST6/00621 grant), Poland.
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Les, T., Markiewicz, T., Dziekiewicz, M., Lorent, M. (2019). A Flood-Fill-Based Technique for Boundary Closure of Kidney Contours in CT Images. In: Laukaitis, G. (eds) Recent Advances in Technology Research and Education. INTER-ACADEMIA 2018. Lecture Notes in Networks and Systems, vol 53. Springer, Cham. https://doi.org/10.1007/978-3-319-99834-3_30
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DOI: https://doi.org/10.1007/978-3-319-99834-3_30
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