In cell images the clustering phenomenon frequently appears. In order to separate the clustering cells

an automatic segmentation algorithm based on a novelB2spline active contourmodel (B2Snakemodel) is proposed. The novel B Snake’s energy terms depend notonly on the cell image itself butalso on amodified nonlineardistance image. Firstly

the algorithm generates the distance image. The distance image is called a nonlinear distance image because of the nonlinear relationship between the gray levels ateach pixel and the distance from thatpixel to its nearest background pixel. To produce themodified nonlinear distance image

an iterative erosion method with a dynamic structure rather than a fixed one is used in the algorithm. Secondly

the B Ssnake model is initiated via morphological operation on the modified nonlinear distance image. Two initializationmethods

one is faster but the other ismore precise

can be chosen according to the cell types in the cell images. Finally

the novelB2Snakemodel obtains the cell boundaries under the effect of both the original image force and the modified nonlinear distance image force. Experimental results show that our algorithm is effective for automatic cell image segmentation.