@article{Boroomand_Deglint_Wong_2016, title={Bayesian Compensated Microscopy}, volume={2}, url={https://openjournals.uwaterloo.ca/index.php/vsl/article/view/108}, DOI={10.15353/vsnl.v2i1.108}, abstractNote={<p>We present a novel Bayesian compensated microscopy (BCM) technique<br />designed for enhancing microscopy image quality. The proposed<br />BCM technique provides a computational approach to jointly<br />compensate for microscopy image degradations due to (1) optical<br />aberrations, (2) illumination non-uniformities, and (3) imaging noise<br />within a probabilistic framework. Experimental results based on a<br />stained pathology sample of spleen tissue with leukemia demonstrate<br />the effectiveness of the proposed BCM technique for the<br />quality enhancement in microscopy imaging. The proposed BCM<br />technique can lead to improved visualization of fine tissue structures<br />as well as a more consistent visualization across the entire<br />sample, which can be beneficial for accurate analysis and better<br />interpretation of microscopy samples.</p>}, number={1}, journal={Journal of Computational Vision and Imaging Systems}, author={Boroomand, Ameneh and Deglint, Jason and Wong, Alexander}, year={2016}, month={Oct.} }