In this paper we propose a new method for cells segmentation in HEp-2 images addressing and overcoming the main limitations of the existing approaches. The proposed method adopts image reconstruction for a preliminary image segmentation and, then, it employs a sort of classifier-controlled dilation for better determining the structure of the cells, where the classifier is trained using data of the image at hand. We compare the performance of the proposed method with the most representative approaches from the scientific literature on a common and publicly available dataset of HEp-2 images.