Calculating curvature through gradient descent and nonlinear regression: A novel mathematical approach to digital anatomical morphometry
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11130%2F23%3A10471011" target="_blank" >RIV/00216208:11130/23:10471011 - isvavai.cz</a>
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=lwNw~bH1pv" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=lwNw~bH1pv</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.imu.2023.101383" target="_blank" >10.1016/j.imu.2023.101383</a>
Alternative languages
Result language
angličtina
Original language name
Calculating curvature through gradient descent and nonlinear regression: A novel mathematical approach to digital anatomical morphometry
Original language description
Background: Angular projection measurements have long been an established approach in anatomical morphometry. However, many described projection angles are in reference to inherently curved structures, often oversimplifying their topologies. Aims: The objective of this study is to develop a quick, quantitative method for determining structural curvature from digital images. We aim to utilize readily-available software and statistical methods to extrapolate curvature from images and compare this new method to established angular measurements. Methods: Projection angulation and curvature was modeled on and assessed by the acromia of 50 dry scapulae. Digital images were taken at a known scale, perpendicular to the acromion, and then processed with ImageJ software. Angles were measured by the angle tool and for curvature, seven markers were placed along the external and internal margins of the acromion. Utilizing Excel's Solver function, the coordinate points were passed through a rotation matrix and optimized for second order regression. Solver was instructed to minimize the sum of squared estimated error between our measured and calculated coordinate values by manipulating the angle of point rotation and regression equation coefficients. Results: Significant differences were found between external, internal, and midline acromion measurements in both angles and curvatures. External angle = 80.8 (14.2)°; internal angle = 130.3 (13.6)°; midline angle = 105.6 (10.5)°; [reported as mean (SD)]. External curvature = 0.055 (0.015) mm-1; internal curvature = 0.035 (0.025) mm-1; midline curvature = 0.046 (0.017) mm-1; [reported as median (IQR)]. Conclusions: Solver allows for researchers and clinicians to quickly characterize morphometric courses and properties of a given structure. Paired with other scalar measurements, curvature can complete the picture of an anatomical structure's pattern.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
30106 - Anatomy and morphology (plant science to be 1.6)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Informatics in Medicine Unlocked
ISSN
2352-9148
e-ISSN
2352-9148
Volume of the periodical
43
Issue of the periodical within the volume
2023
Country of publishing house
GB - UNITED KINGDOM
Number of pages
8
Pages from-to
101383
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85175694548