Abstract
In this paper, we propose a system for the automated classification of liver focal lesions of Computer Tomography (CT) images based on a multi-phase examination protocol. Many visual features are first extracted from the CT-scans and then labelled by a Support Vector Machine classifier. Our dataset contains 95 lesions from 5 types: cysts, adenomas, haemangiomas, hepatocellular carcinomas and metastasis. A Leave-One-Out cross-validation technique allows for classification evaluation. The multi-phase results are compared to the single-phase ones and show a significant improvement, in particular on hypervascular lesions.
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Quatrehomme, A., Millet, I., Hoa, D., Subsol, G., Puech, W. (2013). Assessing the Classification of Liver Focal Lesions by Using Multi-phase Computer Tomography Scans. In: Greenspan, H., Müller, H., Syeda-Mahmood, T. (eds) Medical Content-Based Retrieval for Clinical Decision Support. MCBR-CDS 2012. Lecture Notes in Computer Science, vol 7723. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36678-9_8
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DOI: https://doi.org/10.1007/978-3-642-36678-9_8
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