Vertebra segmentation and labeling
About
Interfaces
This algorithm implements all of the following input-output combinations:
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Model Facts
Summary
Mechanism
This algorithm segments the vertebrae in a CT scan, assigns anatomical labels to each detected vertebra and classifies vertebrae as completely or partially visible in the scan. The underlying method is an iterative fully convolutional neural network, details can be found in the article published in Medical Image Analysis.
The algorithm is trained with a wide variety of CT scans of adults, including cases with compression fractures and pedicle screws.
Validation and Performance
Uses and Directions
This algorithm was developed for research purposes only.
If the processing fails or no vertebra are detected, there is often a problem with the input data, e.g., unsupported format, wrong data type, incomplete header, etc. Check that the image header contains the correct voxel spacing and direction cosine vectors and that the image values are Hounsfield Units (Air = -1000, Water = 0).
Please feel free to contact Nikolas Lessmann for help with trying out the algorithm, or if you would like to use it on a larger set of images.
Warnings
Common Error Messages
Information on this algorithm has been provided by the Algorithm Editors, following the Model Facts labels guidelines from Sendak, M.P., Gao, M., Brajer, N. et al. Presenting machine learning model information to clinical end users with model facts labels. npj Digit. Med. 3, 41 (2020). 10.1038/s41746-020-0253-3