Deep learning-based automated detection and segmentation of bone and traumatic bone marrow lesions from MRI following an acute ACL tear

Callie, Stirling; Nathan, Neeteson; Walker, Richard; Boyd, Steven

doi:10.5281/zenodo.14805833

Published February 4, 2025 | Version v1

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Deep learning-based automated detection and segmentation of bone and traumatic bone marrow lesions from MRI following an acute ACL tear

1. University of Calgary

Contributors

Contact person:

Steven, Boyd¹

Researchers:

1. University of Calgary

A multi-task deep learning approach was used for simultaneous bone and BML segmentation from MRI.

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Files (60.2 MB)

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epoch=2013-step=34222.ckpt md5:da607a8e36c02e49062d81722d891742	12.0 MB	Download
epoch=2013-step=34238.ckpt md5:95baefc7d36d35a1949b7f891c0ae81d	12.0 MB	Download
epoch=2016-step=34277.ckpt md5:88d0fc0021a45754f7269b937b19c01c	12.0 MB	Download
epoch=2016-step=34278.ckpt md5:e2b1cd29f1b97d5950ba983bd4b2a528	12.0 MB	Download
epoch=2065-step=33044.ckpt md5:03c4d2df2631cf47f056db6c30fbb0c4	12.0 MB	Download
hparams.yaml md5:bb21bd673ccb3906b9baecc2196f6887	590 Bytes	Download

Additional details

Repository URL: https://github.com/Bonelab/BML-MRI-segmentation
Programming language: Python
Development Status: Active

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DOI

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Zenodo

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Deep learning-based automated detection and segmentation of bone and traumatic bone marrow lesions from MRI following an acute ACL tear, 178, 108791, 2025.

License: Creative Commons Attribution 4.0 International

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Technical metadata

Created: February 4, 2025
Modified: February 4, 2025

Deep learning-based automated detection and segmentation of bone and traumatic bone marrow lesions from MRI following an acute ACL tear

Creators

Contributors

Contact person:

Researchers:

Description

Files

Files (60.2 MB)

Additional details

Software