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dc.contributor.authorBoges, Daniya
dc.contributor.authorAgus, Marco
dc.contributor.authorMagistretti, Pierre J.
dc.contributor.authorCali, Corrado
dc.date.accessioned2020-08-20T08:15:48Z
dc.date.available2020-08-20T08:15:48Z
dc.date.issued2020-06-30
dc.identifier.citationBoges, D. J., Agus, M., Magistretti, P. J., & Calì, C. (2020). Forget About Electron Micrographs: A Novel Guide for Using for Quantitative Analysis of Dense Reconstructions. Neuromethods, 263–304. doi:10.1007/978-1-0716-0691-9_14
dc.identifier.isbn9781071606902
dc.identifier.isbn9781071606919
dc.identifier.issn1940-6045
dc.identifier.issn0893-2336
dc.identifier.doi10.1007/978-1-0716-0691-9_14
dc.identifier.urihttp://hdl.handle.net/10754/664709
dc.description.abstractWith the rapid evolvement in the automation of serial micrographs, acquiring fast and reliably giga- to terabytes of data is becoming increasingly common. Optical, or physical sectioning, and subsequent imaging of biological tissue at high resolution, offers the chance to postprocess, segment, and reconstruct micro- and nanoscopical structures, and then reveal spatial arrangements previously inaccessible or hardly imaginable with simple, single section, two-dimensional images. In some cases, three-dimensional models highlighted peculiar morphologies in a way that two-dimensional representations cannot be considered representative of that particular object morphology anymore, like mitochondria for instance. Observations like these are taking scientists toward a more common use of 3D models to formulate functional hypothesis, based on morphology. Because such models are so rich in details, we developed tools allowing for performing qualitative, visual assessments, as well as quantification directly in 3D. In this chapter we will revise our working pipeline and show a step-by-step guide to analyze our dataset.
dc.publisherSpringer US
dc.relation.urlhttp://link.springer.com/10.1007/978-1-0716-0691-9_14
dc.rightsArchived with thanks to Springer US
dc.titleForget About Electron Micrographs: A Novel Guide for Using 3D Models for Quantitative Analysis of Dense Reconstructions
dc.typeBook Chapter
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Division
dc.contributor.departmentVisual Computing Center (VCC)
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentBioscience Program
dc.eprint.versionPost-print
dc.contributor.institutionDepartment of Neuroscience “Rita Levi Montalcini”, Neuroscience Institute Cavalieri Ottolenghi, Università degli studi di Torino, Torino, Italy
dc.identifier.volume155
dc.identifier.pages263-304
kaust.personBoges, Daniya
kaust.personAgus, Marco
kaust.personMagistretti, Pierre J.
kaust.personCali, Corrado
dc.identifier.eid2-s2.0-85088440945
dc.date.published-online2020-06-30
dc.date.published-print2020


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