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020 _a9783031524516
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024 7 _a10.1007/978-3-031-52451-6
_2doi
050 4 _aQA440-699
072 7 _aPBM
_2bicssc
072 7 _aMAT012000
_2bisacsh
072 7 _aPBM
_2thema
100 1 _aCruz-Orive, Luis Manuel.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_970739
245 1 0 _aStereology
_h[electronic resource] :
_bTheory and Applications /
_cby Luis Manuel Cruz-Orive.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aXVI, 486 p. 152 illus., 95 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aInterdisciplinary Applied Mathematics,
_x2196-9973 ;
_v59
505 0 _a1 Basic Results of Integral Geometry -- 2 Basic Ideas of Geometric Sampling -- 3 Model and Second-Order Stereology -- 4 Sampling and Estimation for Stereology -- 5 Variance Predictors for Systematic Sampling -- Appendix -- List of Notation -- References -- Author Index -- Subject Index.
520 _aThis book presents a comprehensive set of methods for quantifying geometric quantities such as the volume of a tumor, the total surface area of the alveoli in a lung, the length of plant roots, or of blood vessels, the number of neurons in a brain compartment, the connectivity number of trabecular bone, the mean size of grains in a rock, etc.. The methods, illustrated by twenty solved case studies, are based on properly sampled slices, sections, or projections of the material, observable under light, laser, or electron microscopy, or under non-invasive radiological devices such as ecography, computed tomography, or magnetic resonance imaging. Thus, the input usually consists of flat images, and the output consists of relevant quantities defined in three dimensions. Stereology is the discipline of providing sampling designs which warrant unbiased estimation of the corresponding quantities, that is, estimation with zero mean deviation from the target. Sampling is usually systematic (i.e., with regularly spaced probes), and sparse (as opposed to reconstructions) and it is thereby efficient and easy to implement. Stereology is essentially geometric sampling, grounded on integral geometry. The necessary elements of both disciplines are detailed in textbook style, and may be used for postgraduate courses, or to serve the interest of scientists in general. Hitherto no other book on stereology has appeared which encompasses the theory, methodology, and applications of stereology in an interconnected and comprehensive way. The currently available error variance prediction formulae under systematic sampling, and their (non-obvious) derivation, are all gathered, for the first time, in the last chapter. The exposition is augmented by 127 line drawings for the theory, and 27 color pictures of real materials for the case studies.
650 0 _aGeometry.
_968763
650 0 _aImage processing
_xDigital techniques.
_964228
650 0 _aComputer vision.
650 0 _aAnatomy.
_970740
650 0 _aRadiology.
650 0 _aCancer
_xImaging.
_969161
650 1 4 _aGeometry.
_968763
650 2 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
_965550
650 2 4 _aAnatomy.
_970740
650 2 4 _aRadiology.
650 2 4 _aCancer Imaging.
_969163
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031524509
776 0 8 _iPrinted edition:
_z9783031524523
776 0 8 _iPrinted edition:
_z9783031524530
830 0 _aInterdisciplinary Applied Mathematics,
_x2196-9973 ;
_v59
_970741
856 4 0 _uhttps://doi.org/10.1007/978-3-031-52451-6
912 _aZDB-2-SMA
912 _aZDB-2-SXMS
999 _c57531
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