![]() Schindelin J, Arganda-Carreras I, Frise E et al (2012) Fiji: an open-source platform for biological-image analysis. Gualda EJ, Vale T, Almada P et al (2013) OpenSpinMicroscopy: an open-source integrated microscopy platform. The world’s leading software development platform – GitHub. Social Science Research Network, Rochester, NY Rev Netw Econ 6:2Ĭasson T, Ryan PS (2006) Open standards, open source adoption in the public sector, and their relationship to Microsoft’s market dominance. Gaudeul A (2007) Do open source developers respond to competition? The LATEX case study. ACM Digital Libraryĭima AA, Elliott JT, Filliben JJ et al (2011) Comparison of segmentation algorithms for fluorescence microscopy images of cells: comparison of segmentation algorithms. ![]() Ledda P, Santos LP, Chalmers A (2004) In: New York, NY (ed) A local model of eye adaptation for high dynamic range images. Rev Sci Instrum 74:3597–3619īetzig E, Patterson GH, Sougrat R et al (2006) Imaging intracellular fluorescent proteins at nanometer resolution. Moerner WE, Fromm DP (2003) Methods of single-molecule fluorescence spectroscopy and microscopy. Klar TA, Hell SW (1999) Subdiffraction resolution in far-field fluorescence microscopy. Heim R, Cubitt AB, Tsien RY (1995) Improved green fluorescence. J Cell Comp Physiol 59:223–239Ĭhalfie M, Tu Y, Euskirchen G et al (1994) Green fluorescent protein as a marker for gene expression. Shimomura O, Johnson FH, Saiga Y (1962) Extraction, purification and properties of aequorin, a bioluminescent protein from the luminous hydromedusan, aequorea. Shimomura O, Chalfie M, Tsien RY (2008) Nobel prize chemistry. Nat Methods 9:671–675īetzig E, Hell SW, Moerner WE (2014) Nobel prize chemistry. Schneider CA, Rasband WS, Eliceiri KW (2012) NIH image to ImageJ: 25 years of image analysis. In addition, we briefly discuss recent efforts and approaches aimed to share and compare algorithms and introduce software and data sharing good practices as a promising strategy to facilitate reproducibility, software understanding, and optimal software choice for a given scientific problem in the future. We focus on the programs that are, to our knowledge, the most relevant and widely used in the field of light microscopy, as well as the most commonly used within our facility. Even more, we outline the history of ImageJ as it has served as a role model for the development of more recent software packages. We introduce both the general OSS idea as well as some programs used for image analysis. In the following chapter, we briefly sketch the advantages of the open source software (OSS) particularly used for image analysis in the field of life sciences. This overwhelming range of offer difficults the fact of making a reasonable choice, especially to newcomers. Visiting the Bio Imaging Search Engine (BISE) (Bio, BISE, Engine,, Imaging, Search) website at the time of writing this article, almost 1200 open source assets (components, workflows, collections) were found.
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