We present a combined report on the results of three editions of the Cell Tracking Challenge, an ongoing initiative aimed at promoting the development and objective evaluation of cell tracking algorithms. With twenty-one participating algorithms and a data repository consisting of thirteen datasets of various microscopy modalities, the challenge displays today’s state of the art in the field. We analyze the results using performance measures for segmentation and tracking that rank all participating methods. We also analyze the performance of all algorithms in terms of biological measures and their practical usability. Even though some methods score high in all technical aspects, not a single one obtains fully correct solutions. We show that methods that either take prior information into account using learning strategies or analyze cells in a global spatio-temporal video context perform better than other methods under the segmentation and tracking scenarios included in the challenge.
One important index to assess left ventricular diastolic function is the quantitative measurement of atrioventricular junction (AVJ) motion in one cardiac cycle including systole and diastole. The best way to perform the measurement is to use a software tool that can conduct AVJ motion tracking from cine cardiovascular magnetic resonance (CMR) images. In this paper, a software tool for this purpose is presented by using the insight segmentation and registration toolkit (ITK), the visualization toolkit (VTK), and Qt. We propose a surface area-based tracking approach in the software tool. In the tracking approach to obtain the surface area swept by six points being tracked, we manually select six points from four-, three- and two-chamber views of CMR images. After that, we reconstruct the 3-D coordinates of the six points from image acquisition parameters extracted from DICOM files. We perform interpolation by using parametric cubic curve fitting techniques. From the curve fitting results, we finally obtain the surface areas for all time points in one cardiac cycle. The software tool has been successfully implemented. The functionality include single point-based tracking, surface area-based tracking by using 6 tracked points, generation of displacement, sweep surface area and velocity, and generation of tracking movies. From the software engineering practice, it is concluded that ITK, VTK, and Qt are very handy software systems to implement automatic image analysis functions for CMR images, such as quantitative measure of motion by visual tracking. The software tool provides a convenient and efficient way to measure AVJ motion and extends the scope of methods for ventricular function assessment.
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