In order to understand the development of stem cells into specialized mature cells it is necessary to study the growth of cells in culture. For this purpose it is very useful to have an efficient computerized cell tra...In order to understand the development of stem cells into specialized mature cells it is necessary to study the growth of cells in culture. For this purpose it is very useful to have an efficient computerized cell tracking system. In this paper a prototype system for tracking neural stem cells in a sequence of images is described. In order to get reliable tracking results it is important to have good and robust segmentation of the cells. To achieve this we have implemented three levels of segmentation. The primary level, applied to all frames, is based on fuzzy threshold and watershed segmentation of a fuzzy gray weighted distance transformed image. The second level, applied to difficult frames where the first algorithm seems to have failed, is based on a fast geometric active contour model based on the level set algorithm. Finally, the automatic segmentation result on the crucial first frame can be interactively inspected and corrected. Visual inspection and correction can also be applied to other frames but this is generally not needed. For the tracking all cells are classified into inactive, active, dividing and clustered cells. Different algorithms are used to deal with the different cell categories. A special backtracking step is used to automatically correct for some common errors that appear in the initial forward tracking process.展开更多
根据Level-Set方法和VOF方法的优缺点,近年来兴起了一类界面追踪的耦合方法——CLSVOF(Coupled Level-Set and Volume-of-Fluid Method)方法。本文阐述了该方法的耦合实现过程,通过旋转流场和剪切流场2个算例验证了CLSVOF方法相比Level-...根据Level-Set方法和VOF方法的优缺点,近年来兴起了一类界面追踪的耦合方法——CLSVOF(Coupled Level-Set and Volume-of-Fluid Method)方法。本文阐述了该方法的耦合实现过程,通过旋转流场和剪切流场2个算例验证了CLSVOF方法相比Level-Set方法实现了计算过程中的物理量守恒,克服了VOF方法难以准确计算界面的法向和曲率的缺点。使用该方法对溃坝模型进行计算,并将数值模拟结果进行对比分析。结果表明:CLSVOF方法计算结果更加接近于实验结果,该方法相比其他界面追踪方法具有更高的运动界面追踪分辨率。由此说明CLSVOF方法模拟具有自由表面流动工程实际问题的精确性和可行性。展开更多
根据Level-Set方法和VOF方法各自的优缺点,耦合生成一种Level-Set和VOF的耦合界面追踪方法,简称CLSVOF(Coupled Level Set and Volume Of Fluid Method)方法。CLSVOF方法利用Level-Set函数计算VOF体积份额,克服了VOF方法难以准确计算界...根据Level-Set方法和VOF方法各自的优缺点,耦合生成一种Level-Set和VOF的耦合界面追踪方法,简称CLSVOF(Coupled Level Set and Volume Of Fluid Method)方法。CLSVOF方法利用Level-Set函数计算VOF体积份额,克服了VOF方法难以准确计算界面的法向量和曲率的缺点;同时又利用VOF体积份额修正Level-Set函数,克服了Lev-el-Set方法在计算过程中有物理量的损失的缺点。用旋转流场和剪切流场的数值算例验证了CLSVOF方法相比VOF方法提高了运动界面追踪的分辨率,相比Level-Set方法实现了计算过程中的物理量守恒。运用CLSVOF方法数值模拟了两个多介质流运动界面算例,分别是自由剪切层问题和气泡在静止水体中上升问题.对比数值模拟结果与理论分析和实验结果可知CLSVOF方法能精确地追踪多介质流运动界面。展开更多
This paper proposes a novel implementation of the level set method that achieves real-time level-set-based object tracking. In the proposed algorithm, the evolution of the curve is realized by simple operations such a...This paper proposes a novel implementation of the level set method that achieves real-time level-set-based object tracking. In the proposed algorithm, the evolution of the curve is realized by simple operations such as switching values of the level set functions and there is no need to solve any partial differential equations (PDEs). The object contour could change due to the change in the location, orientation or due to the changeable nature of the object shape itself. Knowing the contour, the average color value for the pixels within the contour could be found. The estimated object color and contour in one frame are the bases for locating the object in the consecutive one. The color is used to segment the object pixels and the estimated contour is used to initialize the deformation process. Thus, the algorithm works in a closed cycle in which the color is used to segment the object pixels to get the object contour and the contour is used to get the typical-color of the object. With our fast algorithm, a real-time system has been implemented on a standard PC. Results from standard test sequences and our real time system are presented.展开更多
文摘In order to understand the development of stem cells into specialized mature cells it is necessary to study the growth of cells in culture. For this purpose it is very useful to have an efficient computerized cell tracking system. In this paper a prototype system for tracking neural stem cells in a sequence of images is described. In order to get reliable tracking results it is important to have good and robust segmentation of the cells. To achieve this we have implemented three levels of segmentation. The primary level, applied to all frames, is based on fuzzy threshold and watershed segmentation of a fuzzy gray weighted distance transformed image. The second level, applied to difficult frames where the first algorithm seems to have failed, is based on a fast geometric active contour model based on the level set algorithm. Finally, the automatic segmentation result on the crucial first frame can be interactively inspected and corrected. Visual inspection and correction can also be applied to other frames but this is generally not needed. For the tracking all cells are classified into inactive, active, dividing and clustered cells. Different algorithms are used to deal with the different cell categories. A special backtracking step is used to automatically correct for some common errors that appear in the initial forward tracking process.
文摘根据Level-Set方法和VOF方法的优缺点,近年来兴起了一类界面追踪的耦合方法——CLSVOF(Coupled Level-Set and Volume-of-Fluid Method)方法。本文阐述了该方法的耦合实现过程,通过旋转流场和剪切流场2个算例验证了CLSVOF方法相比Level-Set方法实现了计算过程中的物理量守恒,克服了VOF方法难以准确计算界面的法向和曲率的缺点。使用该方法对溃坝模型进行计算,并将数值模拟结果进行对比分析。结果表明:CLSVOF方法计算结果更加接近于实验结果,该方法相比其他界面追踪方法具有更高的运动界面追踪分辨率。由此说明CLSVOF方法模拟具有自由表面流动工程实际问题的精确性和可行性。
基金Supported by National Natural Science Foundation of China (51175001)Introduce Talented Person of Anhui University of Technology and Science (2009YQQ009)Young Talents in College of Anhui Province (2011SQRL169)
文摘根据Level-Set方法和VOF方法各自的优缺点,耦合生成一种Level-Set和VOF的耦合界面追踪方法,简称CLSVOF(Coupled Level Set and Volume Of Fluid Method)方法。CLSVOF方法利用Level-Set函数计算VOF体积份额,克服了VOF方法难以准确计算界面的法向量和曲率的缺点;同时又利用VOF体积份额修正Level-Set函数,克服了Lev-el-Set方法在计算过程中有物理量的损失的缺点。用旋转流场和剪切流场的数值算例验证了CLSVOF方法相比VOF方法提高了运动界面追踪的分辨率,相比Level-Set方法实现了计算过程中的物理量守恒。运用CLSVOF方法数值模拟了两个多介质流运动界面算例,分别是自由剪切层问题和气泡在静止水体中上升问题.对比数值模拟结果与理论分析和实验结果可知CLSVOF方法能精确地追踪多介质流运动界面。
文摘This paper proposes a novel implementation of the level set method that achieves real-time level-set-based object tracking. In the proposed algorithm, the evolution of the curve is realized by simple operations such as switching values of the level set functions and there is no need to solve any partial differential equations (PDEs). The object contour could change due to the change in the location, orientation or due to the changeable nature of the object shape itself. Knowing the contour, the average color value for the pixels within the contour could be found. The estimated object color and contour in one frame are the bases for locating the object in the consecutive one. The color is used to segment the object pixels and the estimated contour is used to initialize the deformation process. Thus, the algorithm works in a closed cycle in which the color is used to segment the object pixels to get the object contour and the contour is used to get the typical-color of the object. With our fast algorithm, a real-time system has been implemented on a standard PC. Results from standard test sequences and our real time system are presented.
