Forget About Electron Micrographs: A Novel Guide for Using 3D Models for Quantitative Analysis of Dense Reconstructions
Type
Book ChapterKAUST Department
Biological and Environmental Sciences and Engineering (BESE) DivisionVisual Computing Center (VCC)
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Bioscience Program
Date
2020-06-30Online Publication Date
2020-06-30Print Publication Date
2020Permanent link to this record
http://hdl.handle.net/10754/664709
Metadata
Show full item recordAbstract
With 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.Citation
Boges, 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_14Publisher
Springer NatureISBN
97810716069029781071606919
Additional Links
http://link.springer.com/10.1007/978-1-0716-0691-9_14ae974a485f413a2113503eed53cd6c53
10.1007/978-1-0716-0691-9_14