Advanced Image Processing for Biology, and the Open Bio Image Alliance (OBIA)

The field of biological imaging has evolved considerably during the past decade as a result of recent (r)evolutions in fluorescence labeling and optical microscopy. Bioimage informatics has been identified as a top priority to cope with the ever-increasing amount of microscopy data. The challenges and opportunities for researchers in image and signal processing are manyfold. They span the areas of mathematical imaging, with problems such as denoising, 3-D deconvolution and super-resolution localization, as well as image analysis for the segmentation, detection and recognition of biological structures in 3-D. The dynamic aspect of the data requires the development of novel algorithms for tracking fluorescent particles and analyzing high-throughput microscopy data (labeling of cells, phenotyping, extraction of gene expression profiles). A crucial aspect of bioimage informatics is making image analysis tools available to biologists so that they can be applied to real data and used on a routine basis. Developers may benefit from open-source frameworks and international initiative such as OBIA for easying-up this process and creating collaboration networks with biologists.

Published in:
Proceedings of the Twenty-First European Signal Processing Conference (EUSIPCO'13), Marrakech, Kingdom of Morocco

 Record created 2015-09-18, last modified 2020-04-20

External links:
Download fulltextURL
Download fulltextURL
Download fulltextURL
Rate this document:

Rate this document:
(Not yet reviewed)