Abstract
Thyroid disease is extremely common and of concern because of the risk of malignancies and hyper-function and they may become malignant if not diagnosed at the right time. Ultrasound is one of the most often used methods for thyroid nodule detection. However, node detection is very difficult in ultrasound images due to their flaming nature and low quality. In this paper, an algorithm for the formalization of the contour of the nodule using the variance reduction statistic is proposed where cut points are determined, then a method of selecting the nearest neighbor points which form the shape of the nodule is generated, later B-spline method is applied to improve the accuracy of the curve shape. The extracted results are been compared with graph_cut and watershed methods for efficiency. Experiments show that the algorithm can improve the accuracy of the appearance of modality and maximum significance of data in the images is also protected.
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Acknowledgments
This work is supported by the National Science Foundation of China (No. 61572407) and Technology Planning Project of Sichuan Province (No. 2014SZ0207).
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Alrubaidi, W.M.H., Peng, B., Yang, Y., Chen, Q. (2016). An Interactive Segmentation Algorithm for Thyroid Nodules in Ultrasound Images. In: Huang, DS., Han, K., Hussain, A. (eds) Intelligent Computing Methodologies. ICIC 2016. Lecture Notes in Computer Science(), vol 9773. Springer, Cham. https://doi.org/10.1007/978-3-319-42297-8_11
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DOI: https://doi.org/10.1007/978-3-319-42297-8_11
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