Abstract:Due to the relative transparency of its embryos and larvae, the zebrafish is an ideal model organism for bioimaging approaches in vertebrates. Novel microscope technologies allow the imaging of developmental processes in unprecedented detail, and they enable the use of complex image-based read-outs for highthroughput/high-content screening. Such applications can easily generate Terabytes of image data, the handling and analysis of which becomes a major bottleneck in extracting the targeted information. Here, w… Show more
“…Up to date, an assessment of the heart rate is often practiced manually by counting heartbeats from slow motion replay of videotape recordings, what is neither practical for large numbers of hearts to be analyzed nor is it accurate when determining beat-to-beat intervals as needed for detection of arrhythmias. 7 Existing software for semiautomated analysis of heartbeats [7][8][9][10][11][12][13] has several limitations. One is that the embryos have to be anesthetized by adding Tricaine 11,14 or MS-222 12 to avoid movement of zebrafish embryos during videoing.…”
A fully automatic detection and analysis method of heartbeats in videos of nonfixed and nonanesthetized zebrafish embryos is presented. This method reduces the manual workload and time needed for preparation and imaging of the zebrafish embryos, as well as for evaluating heartbeat parameters such as frequency, beat-to-beat intervals, and arrhythmicity. The method is validated by a comparison of the results from automatic and manual detection of the heart rates of wild-type zebrafish embryos 36-120 h postfertilization and of embryonic hearts with bradycardia and pauses in the cardiac contraction.
“…Up to date, an assessment of the heart rate is often practiced manually by counting heartbeats from slow motion replay of videotape recordings, what is neither practical for large numbers of hearts to be analyzed nor is it accurate when determining beat-to-beat intervals as needed for detection of arrhythmias. 7 Existing software for semiautomated analysis of heartbeats [7][8][9][10][11][12][13] has several limitations. One is that the embryos have to be anesthetized by adding Tricaine 11,14 or MS-222 12 to avoid movement of zebrafish embryos during videoing.…”
A fully automatic detection and analysis method of heartbeats in videos of nonfixed and nonanesthetized zebrafish embryos is presented. This method reduces the manual workload and time needed for preparation and imaging of the zebrafish embryos, as well as for evaluating heartbeat parameters such as frequency, beat-to-beat intervals, and arrhythmicity. The method is validated by a comparison of the results from automatic and manual detection of the heart rates of wild-type zebrafish embryos 36-120 h postfertilization and of embryonic hearts with bradycardia and pauses in the cardiac contraction.
“…For the discretization of Eq. (11) we use spatially the 4D Rouy-Tourin scheme [20]. The constrained distance function, which we look for, is obtained as an equilibrium of the numerical solution, i.e.…”
Section: Numerical Methods For Computing the Constrained Distance Funcmentioning
confidence: 99%
“…by a combination of various image processing techniques and manual inspection, for the zebrafish developmental stages up to about one thousand cells [19], there is a great challenge to study embryogenesis at very complex stages of development with thousands of cells present. In [12,22,18,3] new efficient and robust 3D filtering and segmentation algorithms together with a workflow for performing various analyses of such complex developmental stages were suggested and studied.…”
“…to analyze model organisms like mouse [1], zebrafish [2] or fruit fly [3]. An important aim is to reconstruct 3D surfaces or volumes from a set of 2D images called stack.…”
3D segmentation has become a widely used technique. However, automatic segmentation does not deliver high accuracy in optically dense images and manual segmentation lowers the throughput drastically. Therefore, we present a workflow for 3D segmentation being able to forecast segments based on a user-given ground truth. We provide the possibility to correct wrong forecasts and to repeatedly insert ground truth in the process. Our aim is to combine automated and manual segmentation and therefore to improve accuracy by a tunable amount of manual input.
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