AUTOMATIC THYROID NODULE SEGMENTATION AND COMPONENT ANALYSIS IN ULTRASOUND IMAGES

作者：Chang Chuan Yu^*; Huang Hsin Cheng; Chen Shao Jer

来源：Biomedical Engineering - Applications, Basis and Communications, 2010, 22(2): 81-89.

DOI：10.4015/S1016237210001803

• Thyroid nodule segmentation
• Thyroid nodule analysis
• Hierarchical SVM

Heterogeneous thyroid nodules have distinct components and vague boundaries in ultrasound (US) images. It is difficult for radiologists and physicians to manually draw the complete shape of a nodule, or distinguish what kind of components a nodule has. Hence, this article presents an automatic process for nodule segmentation and component classification. A decision-tree algorithm is used to segment the possible nodular area. A refinement process is then applied to recover the nodular shape. Finally, a hierarchical method based on support vector machines (SVMs) is used to identify the components in the nodular lesion. Experimental results of the proposed approach were compared with those of other methods.

• 出版日期2010-4