@inproceedings{606b18878d374747a3ddfd1cc870ec5e,
title = "Refocusing phase contrast microscopy images",
abstract = "Phase contrast microscopy is a very popular non-invasive technique for monitoring live cells. However, its images can be blurred if optics are imperfectly aligned and the visualization on specimen details can be affected by noisy background. We propose an effective algorithm to refocus phase contrast microscopy images from two perspectives: optics and specimens. First, given a defocused image caused by misaligned optics, we estimate the blur kernel based on the sparse prior of dark channel, and non-blindly refocus the image with the hyper-Laplacian prior of image gradients. Then, we further refocus the image contents on specimens by removing the artifacts from the background, which provides a sharp visualization on fine specimen details. The proposed algorithm is both qualitatively and quantitatively evaluated on a dataset of 500 phase contrast microscopy images, showing its superior performance for visualizing specimens and facilitating microscopy image analysis.",
author = "Liang Han and Zhaozheng Yin",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017 ; Conference date: 11-09-2017 Through 13-09-2017",
year = "2017",
doi = "10.1007/978-3-319-66185-8\_8",
language = "英语",
isbn = "9783319661841",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "65--74",
editor = "Pierre Jannin and Simon Duchesne and Maxime Descoteaux and Alfred Franz and Collins, \{D. Louis\} and Lena Maier-Hein",
booktitle = "Medical Image Computing and Computer Assisted Intervention − MICCAI 2017 - 20th International Conference, Proceedings",
address = "德国",
}