Feature analysis and classification of lymph nodes

Authors:
Chuan-Yu Chang;Shu-Han Chang;Shao-Jer Chen
Affiliations:
Department of Computer Science and Information Engineering, National Yunlin University of Science & Technology, Douliou, Yunlin, Taiwan;Department of Computer Science and Information Engineering, National Yunlin University of Science & Technology, Douliou, Yunlin, Taiwan;Department of Medical Imaging, Buddhist Tzu Chi General Hospital, Dalin, Chia-Yi, Taiwan
Venue:
ICCCI'10 Proceedings of the Second international conference on Computational collective intelligence: technologies and applications - Volume Part III
Year:
2010

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Abstract

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.