
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
| 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). | 1 | |
| 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. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
