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Books on the topic 'Morphometric analysis'

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Author: Grafiati
Published: 4 June 2021
Last updated: 25 January 2023

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1

Bennett, Matthew. The cwms of Snowdonia: A morphometric analysis. London: Dept. of Geography, Queen Mary and Westfield College, 1990.

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2

Bookstein, Fred L. Morphometric Tools for Landmark Data: Geometry and Biology. Cambridge: Cambridge University Press, 1992.

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3

Bookstein, Fred L. Morphometric tools for landmark data: Geometry and biology. Cambridge [England]: Cambridge University Press, 1991.

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4

Alexander, Lois F. A morphometric analysis of geographic variation within Sorex monticolus (Insectivora:Soricidae). Lawrence, Kan: Natural History Museum, University of Kansas, 1996.

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5

A morphometric analysis of geographic variation within Sorex monticolus (Insectivora:Soricidae). Lawrence, Kan: Natural History Museum, University of Kansas, 1996.

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6

A morphometric investigation into the origin(s) of anatomically modern humans. Oxford: John and Erica Hedges, 2003.

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7

Boyd, Jennifer Lorraine Roberta. Morphometric analysis as an aid in distinguishing Cervical Intraepithelial Neoplasia Grade III from Invasive Carcinoma. [S.l: The Author], 1992.

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8

Poole, Robert W. A revision and cladistic analysis of the Heliothis virescens species-group (Lepidoptera: Noctuidae) with a preliminary morphometric analysis of Heliothis virescens. Mississippi State, MS: Dept. of Information Services, Division of Agriculture, Forestry and Veterinary Medicine, Mississippi State University, 1993.

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9

Carraway, Leslie N. A morphologic and morphometric analysis of the "Sorex vagrans species complex" in the Pacific Coast region. Lubbock, Tex: Texas Tech University Press, 1990.

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10

Proebstel, Don S. Taxonomic status of cutthroat trout, Rio Grande suckers, and Arkansas darters: Determined through morphometric, meristic, and mitochondrial DNA analysis. [Colorado?: s.n., 1996.

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11

Urban morphometry: Evolution and analysis. New Delhi, India: Research India Press, 2015.

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12

1952-, Zelditch Miriam, ed. Geometric morphometrics for biologists: A primer. Amsterdam: Elsevier Academic Press, 2004.

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13

Ciochon, Russell L. Evolution of the cercopithecoid forelimb: Phylogenetic and functional implications from morphometric analyses. Berkeley: University of California Press, 1993.

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14

Geomorphological analysis of drainage basins: An introduction to morphometry and hydrological parameters. Burdwan: University of Burdwan, 1993.

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15

F, Wilkinson M. H., and Schut F, eds. Digital image analysis of microbes: Imaging, morphometry, fluorometry, and motility techniques and applications. Chichester: Wiley, 1998.

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16

Messieh, S. N. Separation of Atlantic herring (clupea harengus) stocks in the Southern Gulf of St. Lawrence using digitized Otolith Morphometrics and discriminant function analysis. Dartmouth, N.S: Biological Sciences Branch, Scotia-Fundy Region, Dept. of Fisheries and Oceans, Bedford Institute of Oceanography, 1989.

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17

Alexander, Lois F. A morphometric analysis of geographic variation within Sorex monticolus. 1994.

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18

Richtsmeier, J. T., and S. R. Lele. Morphometric Analysis of Landmark Data: A Coordinate Free Approach. Chapman & Hall, 1996.

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19

Bookstein, Fred L. Morphometric Tools for Landmark Data: Geometry and Biology. Cambridge University Press, 1992.

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20

Bookstein, Fred L. Morphometric Tools for Landmark Data: Geometry and Biology. Cambridge University Press, 1997.

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21

Alexander, Lois F. Morphometric Analysis of Geographic Variation Within Sorex Monticolus (Insectivora : Soricidae). Creative Media Partners, LLC, 2018.

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22

Maclean, Alison Fiona. Quaternary segmentation of the Wasatch Fault Zone, Utah: As studied by morphometric discriminant analysis. 1985.

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23

Naslenas, Skaiste. Pre and post-operative CT based morphometric analysis of patients with non-syndromic unilateral coronal synostosis (UCS). 2005.

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24

Carraway, Leslie N. A morphologic and morphometric analysis of the relationships within the "sorex vagrans species complex" in the Pacific coast region. 1989.

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25

Snell, Richard Robbins. Morphometric and genetic affinities of Icelandic gulls: comparative analysis of a secondary contact zone between "Larus argentatus" and "Larus hyperboreus". 1990.

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26

Woelke, Franziska. Morphometric analysis of landslides and slope stability on the north shore of the John Day Reservoir, Columbia River, Oregon and Washington. 1996.

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27

Zelditch, Miriam, Donald Swiderski, David H. Sheets, and William Fink. Geometric Morphometrics for Biologists. Academic Press, 2004.

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28

The effect of age and caloric restriction on the ultrastructure and pattern of lipofuscin accumulation in granule cells of the dentate gyrus of the hippocampus of C3B10RF1 female mice: A morphometric analysis. Ottawa: National Library of Canada, 1998.

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29

Zelditch, Miriam Leah, Donald L. Swiderski, and H. David Sheets. Geometric Morphometrics for Biologists: A Primer. Elsevier Science & Technology Books, 2012.

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30

Zelditch, Miriam Leah, Donald L. Swiderski, and H. David Sheets. Geometric Morphometrics for Biologists: A Primer. Elsevier Science & Technology Books, 2017.

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31

Swiderski, Donald L., Miriam L. Zelditch, and H. H. Sheets. Geometric Morphometrics for Biologists: A Primer. Elsevier Science & Technology Books, 2012.

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32

Fink, William L., Miriam Leah Zelditch, Donald L. Swiderski, and H. David Sheets. Geometric Morphometrics for Biologists: A Primer. Elsevier Science & Technology Books, 2004.

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33

Wilson, Albert Gale. Biogeographic and morphometric analyses of the Plethodon vandykei species group. 1993.

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34

M. H. F. Wilkinson (Editor) and F. Schut (Editor), eds. Digital Image Analysis of Microbes: Imaging, Morphometry, Fluorometry and Motility Techniques and Applications. Wiley, 1998.

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35

Schut, F., and M. H. F. Wilkinson. Digital Image Analysis of Microbes: Imaging, Morphometry, Fluorometry and Motility Techniques and Applications. Wiley & Sons, Incorporated, John, 2008.

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36

Smith, Emma. A functional analysis of molar morphometrics in living and fossil homminoids using 2-D digitized images. 1999.

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37

Boedhoe, Premika S. W., and Odile A. van den Heuvel. The Structure of the OCD Brain. Edited by Christopher Pittenger. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228163.003.0023.

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This chapter summarizes the most consistent findings of structural neuroimaging studies of obsessive-compulsive disorder (OCD), and discusses their relationship within the implicated brain networks. The techniques used in these studies are diverse, and include manual tracing of specific regions of interest, whole-brain voxel-based morphometry (VBM) for both gray matter and white matter volume comparisons, FreeSurfer to investigate differences in cortical thickness and subcortical volumes, and other methods such as covariance analyses. Findings on white matter integrity with tract-based spatial statistics (TBSS) and in diffusion tensor imaging (DTI) studies are discussed as well.The literature shows that the pathophysiology of OCD cannot be explained by alterations in function and structure of the classical cortico-striato-thalamo-cortical (CSTC) regions exclusively, but that fronto-limbic and fronto-parietal connections are important as well, and the role of the cerebellum needs more attention in future research.
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38

Shah, Janak Mahendra. Prog nostic significance of DNA ploidy by flow cytometry and nuclear morphometry by image analysis in 75 cases of breast cancer with axillary lymph node metastases. 1993.

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39

Aspden, Richard, and Jenny Gregory. Morphology. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199668847.003.0011.

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The study of joint morphology can help us to understand the risk factors for osteoarthritis (OA), how it progresses, and aids in developing imaging biomarkers for study of the disease. OA results in gross structural changes in affected joints. Growth of osteophytes, deformation of joint components, and loss of joint space where cartilage has broken down are all characteristics of the disorder. Certain bone shapes as well as malalignment predispose people to future OA, or may be a marker for early OA. Geometrical measures, such as the alpha angle or Wiberg’s CE angle, used to be the primary tool for investigating morphology. In recent years, however, statistical shape modelling (SSM) has become increasingly popular. SSM can be used with any imaging modality and has been successfully applied to a number of musculoskeletal conditions. It uses sets of landmark points denoting the anatomy of one or more bones to generate new variables (modes) that describe and quantify the shape variation in a set of images via principal components analysis. With the aid of automated search algorithms for point placement, the use of SSMs is expanding and provides a valuable and versatile tool for exploration of bone and joint morphometry. Whilst the majority of research has focused on hip and knee OA, this chapter provides an overview of joint morphology through the whole skeleton and how it has helped our ability to understand and quantify the risk and progression of osteoarthritis.
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