Agarwal S (2004) Osteolysis—basic science, incidence and diagnosis. Curr Orthop 18: 220–231. doi:10.1016/j.cuor.2004.03.002
Article
Google Scholar
de Poorter JJ, Hoeben RC, Hogendoorn S, Mautner V, Ellis J, Obermann WR, Huizinga TWJ (2008) Gene therapy and cement injection for restabilization of loosened hip prostheses. Hum Gene Ther 19: 83–95. doi:10.1089/hum.2007.111
PubMed
Article
Google Scholar
Raaijmaakers M, Mulier M (2010) Percutaneous in situ cementation of a loose femoral stem. J Arthroplast 25:1169.e21–1169.e24. doi:10.1016/j.arth.2009.03.027
Cody DD, Gross GJ, Hou J, Spencer HJ, Goldstein SA, Fyhrie DP (1999) Femoral strength is better predicted by finite element models than QCT and DXA. J Biomech 32: 1013–1020. doi:10.1016/S0021-9290(99)00099-8
PubMed
Article
CAS
Google Scholar
Schileo E, Taddei F, Malandrino A, Cristofolini L, Viceconti M (2007) Subject-specific finite element models can accurately predict strain levels in long bones. J Biomech 40: 2982–2989. doi:10.1016/j.jbiomech.2007.02.010
PubMed
Article
Google Scholar
Garcia-Cimbrelo E, Tapia M, Martin-Hervas C (2007) Multislice computed tomography for evaluating acetabular defects in revision THA. Clin Orthop Relat Res 463: 138–143. doi:10.1097/BLO.0b013e3181566320
PubMed
Google Scholar
Walde TA, Weiland DE, Leung SB, Kitamura N, Sychterz CJ, Engh CA, Claus AM, Potter HG (2005) Comparison of CT, MRI, and radiographs in assessing pelvic osteolysis: a cadaveric study. Clin Orthop Relat Res 437: 138–144. doi:10.1097/01.blo.0000164028.14504.46
PubMed
Article
Google Scholar
Cahir JG, Toms AP, Marshall TJ, Wimhurst J (2007) CT and MRI of hip arthroplasty. Clin Radiol 62: 1163–1171. doi:10.1016/j.crad.2007.04.018
PubMed
Article
CAS
Google Scholar
Watzke O, Kalender W (2004) A pragmatic approach to metal artifact reduction in CT: merging of metal artifact reduced images. Eur Radiol 14: 849–856. doi:10.1007/s00330-004-2263-y
PubMed
Article
Google Scholar
Liu P, Pavlicek W, Peter M, Spangehl M, Roberts C, Paden R (2009) Metal artifact reduction image reconstruction algorithm for CT of implanted metal orthopedic devices: a work in progress. Skeletal Radiol 38: 797–802. doi:10.1007/s00256-008-0630-5
PubMed
Article
Google Scholar
Zoroofi RA, Sato Y, Sasama T, Nishii T, Sugano N, Yonenobu K, Yoshikawa H, Ochi T, Tamura S (2003) Automated segmentation of acetabulum and femoral head from 3-D CT images. IEEE Trans Inf Technol Biomed 7: 329–343. doi:10.1109/TITB.2003.813791
PubMed
Article
Google Scholar
Kang Y, Engelke K, Kalender WA (2003) A new accurate and precise 3-D segmentation method for skeletal structures in volumetric CT data. IEEE Trans Med Imaging 22: 586–598. doi:10.1109/TMI.2003.812265
PubMed
Article
Google Scholar
Yokota F, Okada T, Takao M, Sugano N, Tada Y, Sato Y (2009) Automated segmentation of the femur and pelvis from 3D CT data of diseased hip using hierarchical statistical shape model of joint structure. Med Image Comput Comput Assist Interv 12: 811–818. doi:10.1007/978-3-642-04271-3_98
PubMed
Google Scholar
Shlens J (2005) A tutorial on principal component analysis. Systems Neurobiology Laboratory, Salk Institute for Biological Studies. http://www.snl.salk.edu/~shlens/pca.pdf. Accessed 16 Nov 2011
Sharma N, Aggarwal LM (2010) Automated medical image segmentation techniques. J Med Phys 35: 3–14. doi:10.4103/0971-6203.58777
PubMed
Article
Google Scholar
Malan DF, Botha CP, Nelissen RGHH, Valstar ER (2010) Voxel classification of periprosthetic tissues in clinical computed tomography of loosened hip prostheses. In: Proceedings of the IEEE international symposium on biomedical imaging: from nano to macro, Rotterdam, The Netherlands, pp 1341–1344
Boykov Y, Veksler O, Zabih R (2001) Fast approximate energy minimization via graph cuts. IEEE Trans Pattern Anal Mach Intell 23: 1222–1239. doi:10.1109/34.969114
Article
Google Scholar
Delong A, Boykov Y (2009) Globally optimal segmentation of multi-region objects. In: Proceedings of the IEEE 12th international computer vision conference, Kyoto, Japan, pp 285–292
Veksler O (2010) Code: multi-label optimization. University of Western Ontario. http://vision.csd.uwo.ca/code/. Accessed 22 Sept 2010
Maleike D, Nolden M, Meinzer HP (2009) Interactive segmentation framework of the medical imaging interaction toolkit. Comput Methods Programs Biomed 96: 72–83. doi:10.1016/j.cmpb.2009.04.004
PubMed
Article
CAS
Google Scholar
van der Lijn F, den Heijer T, Breteler MMB (2008) Hippocampus segmentation in MR images using atlas registration, voxel classification, and graph cuts. Neuroimage 43: 708–720. doi:10.1016/j.neuroimage.2008.07.058
PubMed
Article
Google Scholar
Zou KH, Warfield SK, Bharatha A, Tempany CMC, Kaus MR, Haker SJ, Wells WM, Jolesz FA, Kikinis R (2004) Statistical validation of image segmentation quality based on a spatial overlap index. Acad Radiol 11: 178–189. doi:10.1016/S1076-6332(03)00671-8
PubMed
Article
Google Scholar
Kalender WA, Hebel R (1987) Reduction of CT artifacts caused by metallic implants. Radiology 164: 576–577
PubMed
CAS
Google Scholar
Botha CP (2008) Hybrid scheduling in the DeVIDE dataflow visualisation environment. In: Hauser H, Strassburger S, Theisel H (eds) Proceedings of simulation and visualization, pp 309–322
Loog M, van Ginneken B (2006) Segmentation of the posterior ribs in chest radiographs using iterated contextual pixel classification. IEEE Trans Med Imaging 25: 602–611. doi:10.1109/TMI.2006.872747
PubMed
Article
Google Scholar
Folkesson J, Dam EB, Olsen OF, Pettersen PC (2007) Segmenting articular cartilage automatically using a voxel classification approach. IEEE Trans Med Imaging 26: 106–115
PubMed
Article
Google Scholar
van Rikxoort EM, de Hoop B, van de Vorst S, Prokop M (2009) Automatic segmentation of pulmonary segments from volumetric chest CT scans. IEEE Trans Med Imaging 28: 621–630. doi:10.1109/TMI.2008.2008968
PubMed
Article
Google Scholar
Paclik P, Lai C (2011) PRSD Studio. PR Sys Design, Delft, The Netherlands. http://www.prsdstudio.com/. Accessed 16 Nov 2011
Greig DM, Porteous BT (1989) Exact maximum a posteriori estimation for binary images. J R Stat Soc Ser B Stat Methodol 51: 271–279
Google Scholar
Ahuja RK, Magnanti TL, Orlin JB (1993) Maximum flows: polynomial algorithms. In: Janzow P, Peterson M (eds) Network flows. Prentice Hall, Englewood Cliffs, New Jersey, p 240
Boykov Y, Kolmogorov V (2004) An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision. IEEE Trans Pattern Anal Mach Intell 26: 1124–1137. doi:10.1109/TPAMI.2004.60
PubMed
Article
Google Scholar
Kolmogorov V, Zabin R (2004) What energy functions can be minimized via graph cuts?. IEEE Trans Pattern Anal Mach Intell 26: 147–159. doi:10.1109/TPAMI.2004.1262177
PubMed
Article
Google Scholar
Egger J, Colen RR, Freisleben B, Nimsky C (2011) Manual refinement system for graph-based segmentation results in the medical domain. J Med Syst. doi:10.1007/s10916-011-9761-7
Schwarz EM, Campbell D, Totterman S, Boyd A, O’Keefe RJ (2003) Use of volumetric computerized tomography as a primary outcome measure to evaluate drug efficacy in the prevention of peri-prosthetic osteolysis: a 1-year clinical pilot of etanercept vs. placebo. J Orthop Res 21: 1049–1055. doi:10.1016/S0736-0266(03)00093-7
PubMed
Article
CAS
Google Scholar
Malan DF, Botha CP, Kraaij G, Joemai RM, van der Heide HJL, Nelissen RGHH, Valstar ER (2011) Measuring femoral lesions despite CT metal artefacts: a cadaveric study. Skeletal Radiol. doi:10.1007/s00256-011-1223-2