摘要
研究粘连细胞图像的分割问题。针对医学细胞图像中,细胞经常发生粘连,细胞粘连部分由于发生像素灰度混合,造成图像不清晰。传统的应用灰度的分割算法由于不能很好的区分粘连部分的灰度,不能完整的分割细胞的问题。为了解决上述问题,提出了自适应阀值调整的粘连细胞分割方法。通过求得粘连部位的细胞像素的具体特征,运用阀值的自适应变化区分粘连部位像素之间的不同,对像素进行划分,克服了传统方法像素划分不清的弊端。实验表明,方法能够有效的分割医学图像中的粘连细胞,取得了比较好的效果。
Research adhesion cell image segmentationd. Inmedical cell images, dues to the mixing of pixels gray scales, cells adhesion often happen, and the traditional gray level based algorithm cannot complete segmentation well. In order to solve this problem, this paper proposed a cell segmentation method based on adaptive threshold adjustment. Through the specific features of the pixels of cell adhesion, the the adaptive change of the threshold was used to distinguish different parts of the adhesion pixels, which can overcome the drawbacks of traditional method. The experiments show that the method can effectively segment medical images of adhesion cells and achieve good resuits
出处
《计算机仿真》
CSCD
北大核心
2012年第2期260-262,272,共4页
Computer Simulation
关键词
粘连细胞
细胞分割
自适应阀值
Adhesion cells
Cells segmentation
Adaptive threshold
