Abstract
Nowadays there are millions of lung cancer patients around the world, and the number is increasing each year. In this context it is essential for medical radiologists and oncologists to properly control cancer evolution and to calculate quantitative values for its characterization. This paper presents a complete system integrating a software tool to improve the monitoring of patients’ lung nodules and a complete stack of algorithms for a mathematical model to accurately calculate their growth/reduction. At the current moment we have a work in progress using a database with four patients who have been successfully tested, and whose nodules have all experienced positive growth, with an average of 31.72% in area growth and 0.28% per day in area growth speed. In the future, the database is expected to be enlarged with more patients so that numerical data can be obtained for use in statistical studies and mathematical modeling.
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García Arroyo, J.L., García Zapirain, B., Méndez Zorrilla, A. (2011). Quantitative Study and Monitoring of the Growth of Lung Cancer Nodule Using an X-Ray Computed Tomography Image Processing Tool. In: Cabestany, J., Rojas, I., Joya, G. (eds) Advances in Computational Intelligence. IWANN 2011. Lecture Notes in Computer Science, vol 6692. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21498-1_10
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DOI: https://doi.org/10.1007/978-3-642-21498-1_10
Publisher Name: Springer, Berlin, Heidelberg
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