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ZENODO
Software . 2025
Data sources: ZENODO
ZENODO
Software . 2025
Data sources: Datacite
ZENODO
Software . 2025
Data sources: Datacite
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Machine Learning Code for Measurement of Kyphosis and Lordosis in DXA Scans

Authors: Ruby, J. Graham;

Machine Learning Code for Measurement of Kyphosis and Lordosis in DXA Scans

Abstract

Measurement of Kyphosis and Lordosis from Dexa Scans Overview This tool applies ML models to the analysis of DEXA images for measuring curvature at the upper (thoracic) spine (kyphosis), or bottom (lumbar) spine (lordosis). Kyphosis/Lordosis: Methods Description Developer Documentation Installation The recommended build environment for the code is to have Anaconda installed and then to create a conda environment for python 3 as shown below: conda create -n kypho python=3.7 Once created, activate the environment and install all the needed libraries as follows: conda activate kypho pip install -r requirements.txt Usage An example for a recommended invokation of the code, to measure kyphosis: python spineCurve.py -i -o --aug_flip --aug_tilt 0.5 ...or to measure lordosis: python spineCurve.py -i -o --aug_flip --aug_tilt 0.5 --lumbar Detailed Usage Instructions

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average