Segmentation of biological images is a challenging task, due to non convex shapes, intensity inhomogeneity and clustered cells. To address these issues, a new algorithm is proposed based on the B-spline level set method. The implicit function of the level set is modelled as a continuous parametric function represented with the B-spline basis. It is different from the discrete formulation associated with conventional level set. In this paper the proposed framework takes into account properties of biological images. The algorithm is applied to Drosophila images, and compared to conventional level set and Marker Controlled Watershed (MCW). Results show good performance in term of the DICE coefficient, for noisy and noiseless images