\input zb-basic
\input zb-ioport
\iteman{io-port 05845050}
\itemau{Chang, Chuan-Yu; Chang, Shu-Han; Chen, Shao-Jer}
\itemti{Feature analysis and classification of lymph nodes.}
\itemso{Pan, Jeng-Shyang (ed.) et al., Computational collective intelligence. Technologies and applications. Second international conference, ICCCI 2010, Kaohsiung, Taiwan, November 10--12, 2010. Proceedings, Part III. Berlin: Springer (ISBN 978-3-642-16695-2/pbk). Lecture Notes in Computer Science 6423. Lecture Notes in Artificial Intelligence, 1-10 (2010).}
\itemab
Summary: Pathological changes in lymph nodes (LN) can be diagnosed using biopsy, which is a time consuming process. Compared to biopsy, sonography is a better material for detecting pathology in the LN. However, there is lack of consistency between different ultrasound systems, which tend to produce images with different properties. To overcome this problem, a method was proposed in this paper to identify and select universal imaging features to standardize the classification of LN for different ultrasound imaging systems. This will help in the diagnosis of various pathological conditions. The support vector machine (SVM), which combines correlation and performance analysis for the selection of proper imaging features, was adopted for this classification system. Experimental results demonstrated that each selected feature set could be used to classify respective pathological conditions in the LN for images acquired from different ultrasound imaging machines.
\itemrv{~}
\itemcc{}
\itemut{Lymph nodes; Ultrasound image; Feature selection; Classification; Support Vector Machine; Correlation analysis}
\itemli{doi:10.1007/978-3-642-16696-9\_1}
\end