Automated CT bone segmentation using statistical shape modelling and local template matching

References

• Ababneh SY, Prescott JW, Gurcan MN. 2011. Automatic graph-cut based segmentation of bones from knee magnetic resonance images for osteoarthritis research. Med Image Anal. 15(4):438–448.
   PubMed Web of Science ®Google Scholar
• Abler D, Steve B, Terrier A, Fabio B, Alain F, Büchler P. 2018. A statistical shape model to predict the premorbid glenoid cavity. J Shoulder Elb Surg. 27(10):1800–1808
   PubMed Web of Science ®Google Scholar
• Albrecht T, Lüthi M, Gerig T, Vetter T. 2013. Posterior shape models. Med Image Anal. 17:959–973.
   Google Scholar
• Chu C, Bai J, Wu X, Zheng G. 2015. MASCG: Multi-atlas segmentation constrained graph method for accurate segmentation of hip CT images. Med Image Anal. 26(1):173–184.
   PubMed Web of Science ®Google Scholar
• Cootes TF, Taylor CJ, Cooper DH, Graham J. 1995. Active shape models-their training and application. Comput Vis Image Underst. 61:38–59.
   Google Scholar
• Durrleman S, Prastawa M, Charon N, Korenberg JR, Joshi S, Gerig G, Trouvé A. 2014. Morphometry of anatomical shape complexes with dense deformations and sparse parameters. Neuroimage. 101:35–49.
   PubMed Web of Science ®Google Scholar
• Erdt M, Kirschner M, Wesarg S. 2009. Simultaneous segmentation and correspondence establishment for Statistical Shape Models. In: Magnenat-Thalmann N, editor. Modelling the physiological human. 3DPH 2009. Lecture Notes in Computer Science. Vol. 5903. Berlin, Heidelberg: Springer. p. 25–35.
   Google Scholar
• Fu Y, Liu S, Li H, Yang D. 2017. Automatic and hierarchical segmentation of the human skeleton in CT images. Phys Med Biol. 62(7):2812–2833.
   PubMed Web of Science ®Google Scholar
• Heimann T, Meinzer HP. 2009. Statistical shape models for 3D medical image segmentation: A review. Med Image Anal. 13(4):543–563.
   PubMed Web of Science ®Google Scholar
• Janssens R, Zeng G, Zheng G. 2017. Fully automatic segmentation of lumbar vertebrae from ct images using cascaded 3D fully convolutional networks. CoRR. Available from: http://arxiv.org/abs/1712.01509
   Google Scholar
• Kainmueller D, Lamecker H, Heller MO, Weber B, Hege HC, Zachow S. 2013. Omnidirectional displacements for deformable surfaces. Med Image Anal. 17(4):429–441.
   PubMed Web of Science ®Google Scholar
• Kainmueller D, Lamecker H, Seim H, Zinser M, Zachow S. 2009. Automatic Extraction of Mandibular Nerve and Bone from Cone-Beam CT Data. Med Image Comput Comput Interv MICCAI 2009. 5762:76–83.
   Google Scholar
• Klein A, Warszawski J, Hillengaß J, Maier-Hein KH. 2018. Towards Whole-body CT Bone Segmentation. In: Maier A, Deserno TM, Handels H, Maier-Hein KH, Palm C, Tolxdorff T, editors. Bild für die Medizin 2018. Berlin, Heidelberg: Springe; p. 204–209.
   Google Scholar
• Klein A, Warszawski J, Hillengaß J, Maier-Hein KH. 2019. Automatic bone segmentation in whole-body CT images. Int J CARS. 14(1):21–29.
   Google Scholar
• Lessmann N, van Ginneken B, de Jong PA, Išgum I. 2018. Iterative fully convolutional neural networks for automatic vertebra segmentation. In: ProcSPIE. Vol. 10574. Available from: http://arxiv.org/abs/1804.04383
   Google Scholar
• Lieger O, Schaub M, Taghizadeh E, Büchler P. 2018. How symmetrical are bony orbits in humans? J Oral Maxillofac Surg. 77(1):118–125
   PubMed Web of Science ®Google Scholar
• Litjens G, Kooi T, Bejnordi BE, Setio AAA, Ciompi F, Ghafoorian M, van der Laak J, van Ginneken B, Sánchez CI. 2017. A survey on deep learning in medical image analysis. Med Image Anal. 42:60–88.
   PubMed Web of Science ®Google Scholar
• Lüthi M, Blanc R, Albrecht T, Gass T, Goksel O, Büchler P, Kistler M, Bousleiman H, Reyes M, Cattin P. 2012. Statismo-A framework for PCA based statistical models. Insight J. 1:1–18.
   Google Scholar
• Lüthi M, Jud C, Gerig T, Vetter T. 2016. Gaussian process morphable models. IEEE Trans Pattern Anal Mach Intell. 40(8):1860–1873.
   Web of Science ®Google Scholar
• Mutsvangwa T, Burdin V, Schwartz C, Roux C. 2015. An automated statistical shape model developmental pipeline: application to the human scapula and humerus. IEEE Trans Biomed Eng [Eng]. 62(4):1098–1107.
   PubMed Web of Science ®Google Scholar
• Plessers K, Vanden Berghe P, Van Dijck C, Wirix-Speetjens R, Debeer P, Jonkers I, Vander Sloten J. 2018. Virtual reconstruction of glenoid bone defects using a statistical shape model. J Shoulder Elb Surg. 27(1):160–166.
   PubMed Web of Science ®Google Scholar
• Poltaretskyi S, Chaoui J, Mayya M, Hamitouche C, Bercik MJ, Boileau P, Walch G. 2017. Prediction of the pre-morbid 3D anatomy of the proximal humerus based on statistical shape modelling. Bone Joint J. 99-B(7):927–933.
   PubMedGoogle Scholar
• Rasmussen CE, Williams CKI. 2006. Gaussian Processes for Machine Learning. Cambridge, MA: University Press Group Limited, MIT Press. Available from: http://www.gaussianprocess.org/gpml/chapters/RW.pdf
   Google Scholar
• Rister B, Horowitz MA, Rubin DL. 2017. Volumetric image registration from invariant keypoints. IEEE Trans Image Process. 26(10):4900–4910.
   PubMed Web of Science ®Google Scholar
• Shim H, Chang S, Tao C, Wang J-H, Kwoh CK, Bae KT. 2009. Knee cartilage: efficient and reproducible segmentation on high-spatial-resolution MR images with the semiautomated graph-cut algorithm method. Radiology. 251(2):548–556.
   PubMed Web of Science ®Google Scholar
• Sinha A, Reiter A, Leonard S, Ishii M, Hager GD, Taylor RH. 2017. Simultaneous segmentation and correspondence improvement using statistical modes. Med Imaging 2017 Image Process. 10133: 101331B.
   Google Scholar
• Vlachopoulos L, Lüthi M, Carrillo F, Gerber C, Székely G, Fürnstahl P. 2018. Restoration of the patient-specific anatomy of the proximal and distal parts of the humerus: statistical shape modeling versus contralateral registration method. J Bone Joint Surg Am. 100(8):e50.
   PubMed Web of Science ®Google Scholar
• Zhang J, Liu M, Wang L, Chen S, Yuan P, Li J, Shen S-F, Tang Z, Chen K-C, Xia JJ, Shen D. 2017. Joint Craniomaxillofacial Bone Segmentation and Landmark Digitization by Context-Guided Fully Convolutional Networks. In: Med Image Comput Comput Assist Interv. Vol. 10434. p. 720–728. Available from: http://arxiv.org/abs/1803.11303
   Google Scholar