Intelligent techniques for image segmentation in cell tracking and mobility analysis

Abstract

Segmentation and tracking of cells is important step in cell motility studies. Over the past two decades, researchers have developed powerful methods for detecting and tracking the living cells. To improve the overall living cells tracking systems performance, we focused on developing a novel algorithm for image processing. This paper presents novel image segmentation and tracking system technique to incorporate the advantages of both Topological Alignments and snakes. Where the initial segmentation by Topological Alignments is firstly transformed into the input of the snake model and begins its evolvement to the interested object boundary and analyzes the cells mobility. In our experiments, we compared our algorithm with traditional snake. The results demonstrate that the proposed algorithm achieves accurate tracking for detecting and analyzing the mobility of the living cells. Our results indicate better segmentation and more accurate tracking for detecting and analyzing the mobility of the living cells. We have achieved better tracking and detecting for the cells, also dealing with under and over segmentation.