Multi-step level set method for segmentation of overlapping cervical cells

Automatic segmentation of the overlapping cervical cells is one of the most challenging problems in the medical image analysis. This paper presents a novel multi-step level set (LVS) method for segmenting cytoplasm and nuclei from overlapping cells in a single EDF image produced from Pap smear images of multi-layer cervical cell volumes. The first step segments the clump consisting of free or overlapping cells using a region-and edge-based level set method on the Gaussian filtered image. The second step segments the nuclei by a multi-step level set method from the original image. And finally, the most critical step of cytoplasm segmentation is done using level set method optimized by criteria such as curvature of the cytoplasm, duration of retaining the segmented area of the cytoplasm, edge information and a speed regulator depends on the homogeneity of the cell. The performance of the proposed algorithm is evaluated on the real cervical cell image provided by the second overlapping cervical cytology image segmentation challenge at ISBI 2015. Clump detection shows good result in spite of the weak clump boundary. Nuclei detection also shows good result in spite of congestion of nuclei. We are also able to segment two overlapping cells in the real Pap smear image.