Body Shape Analysis
Body Shape Analysis - Related Videos
09:03
Morphometric Analyses of Shape: The Analysis Software Toolbox for Craniofacial Shape Quantification in Zebrafish
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2026
This work describes a protocol for quantifying craniofacial cartilage shape using free software (tpsDigs2, MorphoJ, and PAST) to measure changes in facial structure in zebrafish larvae.
06:54
Analysis of Pluripotent Stem Cells by using Cryosections of Embryoid Bodies
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Cited by 14 •
2010
Pluripotent stem cells growing in suspension differentiate into embryoid bodies (EBs). Here we demonstrate how to obtain high quality EB cryosections useful for studying cellular and molecular aspects of embryogenesis, while preserving their organization as aggregates.
05:05
Dissection of Human Vitreous Body Elements for Proteomic Analysis
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Cited by 28 •
2011
This video shows an effective technique for differentiating and dissecting the various semi-transparent structures of the human vitreous body in post mortem eyes.
05:33
Three-Dimensional Shape Modeling and Analysis of Brain Structures
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Cited by 2 •
2019
We introduce a semi-automatic protocol for shape analysis on brain structures, including image segmentation using open software, and further group-wise shape analysis using an automated modeling package. Here, we demonstrate each step of the 3D shape analysis protocol with hippocampal segmentation from brain MR images.
03:37
Molecular Shape and Polarity
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2020
Dipole Moment of a Molecule Polar covalent bonds connect two atoms with differing electronegativities, leaving one atom with a partial positive charge (δ+) and the other atom with a partial negative charge (δ–), as the electrons are pulled toward the more electronegative atom. This separation of charge gives rise to a bond dipole moment. The magnitude of a bond dipole moment is represented by the Greek letter mu (µ) and is given by the formula shown here, where Q is the magnitude of the...
FAQs
Different measurements answer different clinical questions. Body mass index summarizes body size, while waist and hip circumferences describe regional proportions; skinfolds and three-dimensional scanning add information about body geometry. Considering these measures together can distinguish overall size from fat distribution or changes in muscle mass and posture, making health evaluation more informative than relying on one dimension alone.
Fat distribution matters because location and pattern can provide information beyond total body size. Waist and hip measurements help characterize regional proportions, while repeated assessments can show changes in adiposity. In medicine, these patterns may support cardiometabolic risk evaluation and help clinicians relate physical form to broader health findings.
Standardization makes measurements more comparable. Applying the same measurement approach across patients, populations, or follow-up visits helps determine whether an observed difference reflects a real change rather than inconsistent assessment. This is particularly useful when tracking growth, treatment outcomes, or changes in nutritional status over time in clinical and research settings.
Choice of measurement or imaging should match the feature being assessed. Waist and hip circumferences quantify proportions, body mass index provides a size-related measure, skinfolds contribute information about body form, and three-dimensional scanning captures body geometry. Using an appropriate combination allows assessment to address adiposity, muscle mass, posture, or overall physical dimensions.
During clinical follow-up, serial body shape measurements can document growth or treatment outcomes rather than serving only as a single baseline description. They may also contribute to nutritional-status assessment and cardiometabolic-risk evaluation. Interpreting the measurements alongside clinical examination helps place numerical changes in a broader medical context.
Body shape data can support studies linking body composition with disease, but the measurements do not replace clinical examination. Their value lies in adding quantitative evidence about dimensions, proportions, and distribution to other clinical information. In research, standardized data also enable comparisons among patients and populations and across different points in time.