Zhou Huiyu, Schaefer Gerald, Celebi M, Iyatomi Hitoshi, Norton Kerri-Ann, Liu Tangwei, Lin Faquan
The Institute of Electronics, Communications and Information Technology (ECIT), Queen's University Belfast, United Kingdom.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:1974-7. doi: 10.1109/IEMBS.2010.5627556.
Accurate identification of lesion borders is an important task in the analysis of dermoscopy images since the extraction of skin lesion borders provides important cues for accurate diagnosis. Snakes have been used for segmenting a variety of medical imagery including dermoscopy, however, due to the compromise of internal and external energy forces they can lead to under- or over-segmentation problems. In this paper, we introduce a mean shift based gradient vector flow (GVF) snake algorithm that drives the internal/external energies towards the correct direction. The proposed segmentation method incorporates a mean shift operation within the standard GVF cost function. Experimental results on a large set of diverse dermoscopy images demonstrate that the presented method accurately determines skin lesion borders in dermoscopy images.
在皮肤镜图像分析中,准确识别病变边界是一项重要任务,因为提取皮肤病变边界为准确诊断提供了重要线索。蛇形模型已被用于分割包括皮肤镜图像在内的各种医学图像,然而,由于内部和外部能量力的折衷,它们可能导致分割不足或过度分割问题。在本文中,我们介绍了一种基于均值漂移的梯度向量流(GVF)蛇形算法,该算法将内部/外部能量引导至正确方向。所提出的分割方法在标准GVF成本函数中纳入了均值漂移操作。在大量不同的皮肤镜图像上的实验结果表明,所提出的方法能够准确确定皮肤镜图像中的皮肤病变边界。