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Product specification: 2D bone segmentation
Product description: BoneFinderTM is a fully automatic annotation tool to outline bone contours and skeletal structures in 2D radiographs. It has been successfully applied to a range of application areas (see also www.bone-finder.com) and several models have been made available. If you would want to discuss the segmentation of alternative skeletal structures, please contact the developers via http://personalpages.manchester.ac.uk/staff/claudia.lindner/
BoneFinderTM is available free of charge for academic research purposes. Please cite the following paper when publishing anything resulting from the usage of BoneFinderTM :
C. Lindner, S. Thiagarajah, J.M. Wilkinson, The arcOGEN Consortium, G.A. Wallis and T.F. Cootes, "Fully Automatic Segmentation of the Proximal Femur Using Random Forest Regression Voting", IEEE Trans. Medical Imaging, Vol. 32, No. 8, pp. 1462-1472, 2013. doi:10.1109/TMI.2013.2258030
In any publications resulting from the usage of the lateral cephalometric model please also cite:
C. Lindner, C-W. Wang, C-T. Huang, C-H. Li, S-W. Chang and T. Cootes, "Fully Automatic System for Accurate Localisation and Analysis of Cephalometric Landmarks in Lateral Cephalograms", Scientific Reports, Vol. 6, Art. Nr. 33581, 2016. doi:10.1038/srep33581
Application areas: quantitative analysis and statistical modelling of bone shape
Product requirements: 32-bit or 64-bit Windows computer with at least 2GB RAM. We recommend the usage of the 64-bit BoneFinder version.
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BoneFinderTM has recently won the first prize in the Dental X-ray Image Analysis ISBI Grand Challenge. Please click here for more details.
Please note that an approved licence is required before commercial files related to this product can be downloaded. Such files are indicated by .
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File description:BoneFinder installation files (excludes models) for computers running a 64-bit version of Windows, ideally with at least 3GB RAM. This is the recommended version of BoneFinder.
File name:BoneFinder_WIN64_v1.2.0.zip
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| File size:7.16 MB | File version:1.2.0 |
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File description:BoneFinder installation files (excludes models) for computers running a 32-bit version of Windows.
File name:BoneFinder_WIN32_v1.2.0.zip
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| File size:6.18 MB | File version:1.2.0 |
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File description:BoneFinder AP proximal femur model for usage with the 64-bit BoneFinder version. This model was trained on 1105 AP pelvic radiographs provided by The arcOGEN Consortium to outline the contours of disease-free proximal femurs using 65 points.
File name:BoneFinder_AP_prox_femur_65pts_models_64bit.zip
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| File size:290.68 MB | File version:1.00 |
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File description:BoneFinder AP proximal femur model for usage with both BoneFinder versions. This model was trained on 1105 AP pelvic radiographs provided by The arcOGEN Consortium to outline the contours of disease-free proximal femurs using 65 points.
File name:BoneFinder_AP_prox_femur_65pts_models.zip
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| File size:148.11 MB | File version:1.00 |
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File description:BoneFinder lateral cephalometric model for usage with both BoneFinder versions. This model was trained on 400 lateral cephalograms (available from https://figshare.com/s/37ec464af8e81ae6ebbf) to outline 19 cephalometric landmarks in children and adults.
File name:BoneFinder_LAT_ceph_19pts_models.zip
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| File size:149.65 MB | File version:1.00 |
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File description:BoneFinder manual (software installation and usage instructions)
File name:BoneFinderManual.pdf
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| File size:805.84 KB | File version:2.00 |
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Lindner , C, Thiagarajah, S, Wilkinson, JM, Wallis, GA, Cootes, TF (2013). "Fully Automatic Segmentation of the Proximal Femur Using Random Forest Regression Voting", IEEE Trans. Medical Imaging Vol. 32, No. 8, 1462-1472.
Lindner, C, Wang, C-W, Huang, C-T, Li, C-H, Chang, S-W, Cootes, T (2016). Fully Automatic System for Accurate Localisation and Analysis of Cephalometric Landmarks in Lateral Cephalograms, Scientific Reports 6, Art. Nr. 33581,.
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CONTACT SUPPORT
BoneFinderTM
A software to determine the shape of bones in X-rays
PROVIDING SCIENTIST/AUTHOR(s)
Dr Claudia Lindner
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