Abstract
Breast MRI segmentation is useful for assisting the clinician to detect suspicious regions. In this paper, an effective approach is proposed for segmenting the breast into different regions, each corresponding to a different tissue. The segmentation work flow comprises three key steps: MR Images preprocessing, locating breast-skin and breast-chest wall boundary by using OTSU thresholding algorithm, and segmenting fibroglandular and fatty tissues with applying the kernel-based fuzzy clustering algorithm (KFCM). The proposed method was applied to segment the clinical breast MR images. Experimental results have been shown visually and achieve reasonable consistency.
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Acknowledgments
Project supported by the National Natural Science Foundation of China (Grant No. 61240010).
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Song, H., Sun, F., Cui, X., Zhu, X., Zhao, Q. (2013). Breast Tissue Segmentation Using KFCM Algorithm on MR images. In: Sun, Z., Deng, Z. (eds) Proceedings of 2013 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38466-0_62
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DOI: https://doi.org/10.1007/978-3-642-38466-0_62
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