Abstract
Prostate cancer is one of the most frequent cancer in men and a major cause of mortality in developed countries. Detection of the prostate carcinoma at an early stage is crucial for a succesfull treatment. In this paper, a method for analysis of transrectal ultrasonography images aimed at computer-aided diagnosis of prostate cancer is presented. Althogh the task is extremely difficult due to a problem of imperfect supervision, we have obtained promising results indicating that valid information for the diagnostic is present in the images. Two classifiers based on k-Nearest Neighbours and Hidden Markov Models are compared.
This work has been partially supported by the Valencian OCYT under grant CTIDIA/2002/80 and by the Spanish CICYT under grant TIC2000-1703-CO3-01.
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Llobet, R., Toselli, A.H., Perez-Cortes, J.C., Juan, A. (2003). Computer-Aided Prostate Cancer Detection in Ultrasonographic Images. In: Perales, F.J., Campilho, A.J.C., de la Blanca, N.P., Sanfeliu, A. (eds) Pattern Recognition and Image Analysis. IbPRIA 2003. Lecture Notes in Computer Science, vol 2652. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-44871-6_48
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DOI: https://doi.org/10.1007/978-3-540-44871-6_48
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