Blood cells and ultrasound contrast agent microbubbles behave strangely when subjected tornan ultrasound ï¬eld. They migrate towards the nodes of the ultrasound wave and form circularrnpatterns. However, differentiation between blood cells and ultrasound contrast agentrnmicrobubbles can be easily determined via time-lapse analysis of the pattern formation. Ultrasoundrncontrast agent microbubbles migrate towards the wave nodes very quickly andrnform tightly packed clusters. In contrast, formation of tightly packed clusters in the case ofrnblood cells is unlikely based on the sonophore model theory of cells. Moreover, the interactionrnof the microbubbles with the blood cells and the surrounding medium is not fully understood.rnTo study the behavior and interaction of sonicated blood cells and microbubblesrnon the time-lapse microscopic images, there is a need to deï¬ne a contour around the cellsrnand the microbubbles. To do so, ï¬rst, the microbubbles and the cells should be segmentedrnfrom the rest of image content. In this regard, this thesis devised a scheme that combines featuresrnof the Laplacian of the Gaussian detector and a modiï¬ed form of the Contrast LimitedrnAdaptive Histogram Equalization (CLAHE) technique for effective analysis of time-lapsernmicroscopic images. The scheme is tested on three datasets (one synthetic and two real) andrnits subjective and objective performance is found quite pleasing. Absence of ground truthrnfor the real datasets makes the evaluation of the segmentation scheme merely subjective.rnObjective evaluation is only performed on the computer-simulated time-lapse images. Thernaverage segmentation sensitivity, speciï¬city and accuracy of the proposed algorithm are valuedrnaround 0.96, 0.91 and 0.95 on the synthetic dataset out of a unit scale, respectively. Thernresult generated could be a crucial input for effective particle tracking and sizing studies.