CAJ | 학술논문

为使细胞分割的结果更加精确,提出一种基于伪中值双边滤波和水平集函数的细胞图像分割方法。首先使用伪中值双边滤波对图像进行预处理,然后利用水平集方法对改进的CV模型进行两次曲线演化,分别得到细胞质与背景分界线,细胞核与细胞质分界线。结果表明：伪中值双边滤波在减弱高斯噪声的同时,同时去除了椒盐噪声,但没有弱化边界,LCV模型在CV模型的基础上添加了局部项,使得对于灰度不均匀的图像分割效果较好。结论：在使用水平集方法进行图像分割之前先进行伪中值双边滤波,同时为CV模型添加局部项,能够增强细胞分割结果的准确性。
위사세포분할적결과경가정학,제출일충기우위중치쌍변려파화수평집함수적세포도상분할방법。수선사용위중치쌍변려파대도상진행예처리,연후이용수평집방법대개진적CV모형진행량차곡선연화,분별득도세포질여배경분계선,세포핵여세포질분계선。결과표명：위중치쌍변려파재감약고사조성적동시,동시거제료초염조성,단몰유약화변계,LCV모형재CV모형적기출상첨가료국부항,사득대우회도불균균적도상분할효과교호。결론：재사용수평집방법진행도상분할지전선진행위중치쌍변려파,동시위CV모형첨가국부항,능구증강세포분할결과적준학성。
In order to obtain more accurate data on cell division,we proposed an image segmentation method based on level set function and pseudomedian bilateral filtering.Cell image was pre-processed by pseudomedian bilateral filtering,then the improved CV model was evoluted twice with level set method. Contour between background and cytoplasm,contour between cytoplasm and nucleus could all be obtained.It has been found that pseudomedian bilateral filtering removed gauss and salt-and-pepper noises, without weakening marginal information.LCV model was added local item on traditional CV model to obtain more accurate segmentation results in cell image with uneven gray levels.This algorithm improved significantly accuracy of cell segmentation.It is concluded that pseudomedian bilateral filtering and addition of local item to CV model could enhance the accuracy of cell image segmentation.