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Diagnostic Support Systems and Computational Intelligence: Differential Diagnosis of Hepatic Lesions from Computed Tomography Images

Diagnostic Support Systems and Computational Intelligence: Differential Diagnosis of Hepatic Lesions from Computed Tomography Images

Stavroula Mougiakakou, Ioannis Valavanis, Alexandra Nikita, Konstantina S. Nikita
Copyright: © 2012 |Pages: 15
ISBN13: 9781609608187|ISBN10: 1609608186|EISBN13: 9781609608194
DOI: 10.4018/978-1-60960-818-7.ch511
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MLA

Mougiakakou, Stavroula, et al. "Diagnostic Support Systems and Computational Intelligence: Differential Diagnosis of Hepatic Lesions from Computed Tomography Images." Machine Learning: Concepts, Methodologies, Tools and Applications, edited by Information Resources Management Association, IGI Global, 2012, pp. 1374-1388. https://doi.org/10.4018/978-1-60960-818-7.ch511

APA

Mougiakakou, S., Valavanis, I., Nikita, A., & Nikita, K. S. (2012). Diagnostic Support Systems and Computational Intelligence: Differential Diagnosis of Hepatic Lesions from Computed Tomography Images. In I. Management Association (Ed.), Machine Learning: Concepts, Methodologies, Tools and Applications (pp. 1374-1388). IGI Global. https://doi.org/10.4018/978-1-60960-818-7.ch511

Chicago

Mougiakakou, Stavroula, et al. "Diagnostic Support Systems and Computational Intelligence: Differential Diagnosis of Hepatic Lesions from Computed Tomography Images." In Machine Learning: Concepts, Methodologies, Tools and Applications, edited by Information Resources Management Association, 1374-1388. Hershey, PA: IGI Global, 2012. https://doi.org/10.4018/978-1-60960-818-7.ch511

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Abstract

Recent advances in computer science provide the intelligent computation tools needed to design and develop Diagnostic Support Systems (DSSs) that promise to increase the efficiency of physicians during their clinical practice. This chapter provides a brief overview of the use of computational intelligence methods in the design and development of DSSs aimed at the differential diagnosis of hepatic lesions from Computed Tomography (CT) images. Furthermore, examples of DSSs developed by our research team for supporting the diagnosis of focal liver lesions from non-enhanced CT images are presented.

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