![]() Machine learning, modeling, visualizationÄ«iological laboratories usually acquire images by measuring photon flux in parallel (using a camera) or sequentially (using a point detector and equipment that scans the area of interest). Our goal is to provide an overview of how open source imaging software can be utilized to provide an end-to-end laboratory solution from acquisition and data storage, to data analysis and data mining ( Table 1). ![]() In this article, representative members of the bioimage informatics community have collaborated to review each computational step that biologists encounter when dealing with digital images, the challenges in that domain, and the overall status of available software for bioimage informatics, focusing on open source options. But with the increased mainstream adoption of advanced optical imaging approaches by biologists and the commitment by funding agencies to prioritize bioimage informatics, there has been a great increase in the number of bioimage informatics 1tools over the last five years. In the quest for breakthroughs of biological significance, biologists are often confronted with the challenge of processing digital data of increasing complexity and richness which demands an informatics infrastructure with tools to collect, store, manipulate, analyze, interpret, and visualize vast amounts of imaging data in a reproducible way with the flexibility to refine aspects of their experimental and imaging techniques in a tight iterative loopÄespite this great need, the bioimage informatics field is still a fairly nascent community compared to the more established hardware development side of the optical microscopy community. In fact, in many cases the computational technology is just as important as the optics not just for the digital capture that all systems now use, but in many cases also for visualizing and properly interpreting the data. ![]() These novel imaging modalities, which are increasingly multi-parametric, rely heavily on computational approaches. ![]() The last twenty years have seen great advances in optical imaging with the ability to monitor biological phenomena with unprecedented resolution, specificity, dimensionality, complexity, and scale, all while maintaining viability and biological relevance. ![]()
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