MAP-MRF Optimal Partitioning for Dynamic Texture Segmentation of Thrombus in Time-Series Microscopic Images

An automatic segmentation of forming thrombus in dynamic microscopic scenes is proposed in this work. We perform a prerequisite temporal partitioning of the image time series and subsequently optimally segment the thrombus region in each frame of the sequence. The partition criterion, which encourages cuts at time points where the areas of the dynamic objects significantly change, is optimized in a MAP-MRF framework. We employ the resulting image intervals to derive maps of dynamic textures, which reveal regions with different temporal behavior. These maps are finally integrated into a level set segmentation, which fuses regional and temporal cues to achieve an accurate result for each frame. Tests on synthetic and real data of zebrafish specimen reveal the high potential of the presented method compared to other approaches.     «

An automatic segmentation of forming thrombus in dynamic microscopic scenes is proposed in this work. We perform a prerequisite temporal partitioning of the image time series and subsequently optimally segment the thrombus region in each frame of the sequence. The partition criterion, which encourages cuts at time points where the areas of the dynamic objects significantly change, is optimized in a MAP-MRF framework. We employ the resulting image intervals to derive maps of dynamic textures, whi...     »