Abstract
In this paper, we describe a computer assisted automatic diagnosis system for lung cancer that detects tumor candidates at an early stage from helical CT images. This automation of the process reduces the time complexity and increases the diagnosis confidence. Our algorithm consists of analysis and diagnosis sections, and detects regions of lung tumor based on image processing techniques and medical knowledge. We have applied our algorithm to 450 patient's data for mass screening. The results show that our algorithm detects lung cancer candidates successfully.
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© 1996 Springer-Verlag Berlin Heidelberg
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Kanazawa, K. et al. (1996). Computer aided screening system for lung cancer based on helical CT images. In: Höhne, K.H., Kikinis, R. (eds) Visualization in Biomedical Computing. VBC 1996. Lecture Notes in Computer Science, vol 1131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0046957
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DOI: https://doi.org/10.1007/BFb0046957
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