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Registration and Segmentation Based Analysis of Microscopy Images Ph D Dissertation, School of Elect

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The document is a thesis by Kevin Lorenz titled 'Registration and Segmentation Based Analysis of Microscopy Images,' submitted for the Doctor of Philosophy degree at Purdue University. It addresses challenges in optical microscopy image analysis, particularly focusing on segmentation and registration techniques to improve the quantification of biological structures in living tissues. The work integrates various image processing methods, including Bayesian estimation, morphological filtering, and non-rigid registration using B-splines, to correct motion artifacts caused by respiration and heartbeat during imaging. The thesis presents experimental results demonstrating the effectiveness of these methods across different biological tissues, highlighting their potential for advancing intravital microscopy as a tool for understanding physiological processes.

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