EPFL | Biomedical Imaging Group | Bioimaging Algorithms

Signal-Processing Algorithms for Bioimaging

D. Sage

Tutorial, Tenth Biennial Conference, 2010 International Conference on Signal Processing and Communications (SPCOM'10), Bangalore, Republic of India, July 18-21, 2010.

In the last decade, images have become indispensable to understand the structure of the cell organisms and revealing their dynamic interactions. Imaging often plays a key role in discoveries in biology. Structures or particles of interest are tagged with fluorescent probes and imaged with a new generation of 3D high-resolution microscopes which produce a large amount of data for quantitative analysis. Automatic processing of these microscopic images remains a challenging task for the image-processing community, one has to handle multidimensional data often corrupted by a defocussing effect, non-uniform lightning, or important noisy and to deal with living particles that rapidly move, grow, interact, or divide. In this tutorial, we describe several algorithms the restoration and analysis of microscopic images of biological organisms. These algorithms are implemented as Java plugins for ImageJ which is the most popular public-domain image-processing software package in the field of bioimaging. We cover the image preparation (correction for drift by registration, correction for photobleaching, correction for non-uniform illumination), the image restoration (extended-of-field procedure, denoising, deconvolution by PSF modelling) and image analysis (feature identification such as spots or filaments, segmentation by parametric active contour, directional analysis, and tracking). These algorithms have been developed by the Biomedical Imaging Group of the EPFL. While they are based on solid signal-processing fundaments, we have made them freely available and accessible to end-users. The presentation includes concepts of algorithms, applications to life cell imaging and live demonstrations.

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