Publications of year 2007

Thesis

1. J. Dowling. Mobility Enhancement using Simulated Artificial Human Vision. PhD thesis, Queensland University of Technology, 2007 .
   

   @PHDTHESIS{2007PhD,
   
    author = {Dowling, J.},
   
    title = {Mobility Enhancement using Simulated Artificial Human Vision},
   
    school = {Queensland University of Technology},
   
    year = {2007}
    
   }
   

Articles in journal or book chapters

1. R. Li and S. Ourselin. Towards Consistently Behaving Deformable Models for Improved Automation in Image Segmentation, chapter 10. Springer Publishers, 2007.
   

   @inBook{Li:Chapter:07,
   
    author = {Li, R. and Ourselin, S.},
   
    title = {Towards Consistently Behaving Deformable Models for Improved Automation in Image Segmentation},
   
    chapter = 10,
   
    journal = {Deformable Models - Theory and Biomaterial Applications},
   
    publisher = {Springer Publishers},
   
    year = 2007,
   
    editor = {Jasjit S Suri and Aly Farag}
    
   }
   



2. P. Bourgeat, J. Fripp, P. Stanwell, S Ramadan, and S. Ourselin. MR image segmentation of the knee bone using phase information. Medical Image Analysis, 11(4):325--335, July 2007.
   

   @Article{Bourgeat:media:07,
   
    author = {Bourgeat, P. and Fripp, J. and Stanwell, P. and Ramadan, S and Ourselin, S.},
   
    title = {MR image segmentation of the knee bone using phase information},
   
    month = {July},
   
    volume = {11},
   
    year = {2007},
   
    pages = {325--335},
   
    journal = {Medical Image Analysis},
   
    number = {4},
   
    publisher = {Elsevier},
   
    url = {http://dx.doi.org/10.1016/j.media.2007.03.003},
   
    
   }
   



3. J. Fripp, P. Bourgeat, S. Crozier, and S.n Ourselin. Shape based segmentation of MRIs of the knee using phase and magnitude information. Academic Radiology, 14(10):1201--1208 , October 2007.
   

   @Article{Fripp2007:AR,
   
    Author = {J. Fripp and P. Bourgeat and S. Crozier and S.n Ourselin},
   
    Title = {Shape based segmentation of MRIs of the knee using phase and magnitude information},
   
    Journal = {Academic Radiology},
   
    Year = {2007},
   
    Volume = {14},
   
    Number = {10},
   
    Month = "October",
   
    Pages = {1201--1208}
    
   }
   



4. J. Fripp, S. Crozier, S. Warfield, and S. Ourselin. Automatic segmentation of the bone and extraction of the bone-cartilage interface from magnetic resonance images of the knee. Physics in Medicine and Biology, 52(6):1617--1631 , March 2007.
   

   @Article{Fripp2007:PMB,
   
    Author = {J. Fripp and S. Crozier and S. Warfield and S. Ourselin},
   
    Title = {Automatic segmentation of the bone and extraction of the bone-cartilage interface from magnetic resonance images of the knee},
   
    Journal = {Physics in Medicine and Biology},
   
    Year = {2007},
   
    Volume = {52},
   
    Number = {6},
   
    Month = "March",
   
    Pages = {1617--1631}
    
   }
   



5. H. Isaksson, O. Comas, C.C. van Donkelaar, J. Mediavilla, W. Wilson, R. Huiskes, and K. Ito. Bone regeneration during distraction osteogenesis: Mechano-regulation by shear strain and fluid velocity. Journal of Biomechanics, 40(9):2002-2011, 2007 .
   

   @article{Isaksson2007JOB,
   
    author={Isaksson, H. and Comas, O. and van Donkelaar, C.C. and Mediavilla, J. and Wilson, W. and Huiskes, R. and Ito, K.},
   
    title = {Bone regeneration during distraction osteogenesis: Mechano-regulation by shear strain and fluid velocity},
   
    journal={Journal of Biomechanics},
   
    volume={40},
   
    number = {9},
   
    pages={2002-2011},
   
    year={2007}
    
   }
   



6. Olivier Salvado and David L. Wilson. Removal of local and biased global maxima in intensity-based registration. Medical Image Analysis, 11:183-196, 2007.

   Abstract:

   Intensity based registration (e.g., mutual information) suffers from a scalloping artifact giving rise to local maxima and sometimes a biased global maximum in a similarity objective function. Here, we demonstrate that scalloping is principally due to the noise reduction filtering that occurs when image samples are interpolated. Typically at a much smaller scale (100 times less in our test cases), there are also fluctuations in the similarity objective function due to interpolation of the signal and to sampling of a continuous, band-limited image signal. Focusing on the larger problem from noise, we show that this phenomenon can even bias global maxima, giving inaccurate registrations. This phenomenon is readily seen when one registers an image onto itself with different noise realizations but is absent when the same noise realization is present in both images. For linear interpolation, local maxima and global bias are removed if one filters the interpolated image using a new constant variance filter for linear interpolation (cv-lin filter), which equalizes the variance across the interpolated image. We use 2D synthetic and MR images and characterize the effect of cv-lin on similarity objective functions. With a reduction of local and biased maxima, image registration becomes more robust and accurate. An efficient implementation adds insignificant computation time per iteration, and because optimization proceeds more smoothly, sometimes fewer iterations are needed.

   
   

   @ARTICLE{salvado_removal_2007,
   
    author = {Olivier Salvado and David L. Wilson},
   
    title = {Removal of local and biased global maxima in intensity-based registration},
   
    journal = {Medical Image Analysis},
   
    year = {2007},
   
    volume = {11},
   
    pages = {183-196},
   
    abstract = {Intensity based registration (e.g., mutual information) suffers from
    a scalloping artifact giving rise to local maxima and sometimes a
    biased global maximum in a similarity objective function. Here, we
    demonstrate that scalloping is principally due to the noise reduction
    filtering that occurs when image samples are interpolated. Typically
    at a much smaller scale (100 times less in our test cases), there
    are also fluctuations in the similarity objective function due to
    interpolation of the signal and to sampling of a continuous, band-limited
    image signal. Focusing on the larger problem from noise, we show
    that this phenomenon can even bias global maxima, giving inaccurate
    registrations. This phenomenon is readily seen when one registers
    an image onto itself with different noise realizations but is absent
    when the same noise realization is present in both images. For linear
    interpolation, local maxima and global bias are removed if one filters
    the interpolated image using a new constant variance filter for linear
    interpolation (cv-lin filter), which equalizes the variance across
    the interpolated image. We use 2D synthetic and MR images and characterize
    the effect of cv-lin on similarity objective functions. With a reduction
    of local and biased maxima, image registration becomes more robust
    and accurate. An efficient implementation adds insignificant computation
    time per iteration, and because optimization proceeds more smoothly,
    sometimes fewer iterations are needed.},
   
    issn = {1361-8415},
   
    keywords = {ACCURATE,Artifact,Cross-correlation,image registration,IMAGES,INFORMATION,interpolation,linear
    interpolation,MR,MR images,MRI,mutual information,Mutual-information,noise,noise
    reduction,noise reduction filtering,optimization,Radiology,REGISTRATION,Scale,TIME,United
    States,Variance},
   
    url = {http://journals.ohiolink.edu/ejc/article.cgi?issn=13618415\&issue=v11i0002\&article=183\_rolabgmiir}
    
   }
   



7. T. Vrtovec, S. Ourselin, L. Gomes, B. Likar, and F Pernus. Automated generation of curved planar reformations from MR images of the spine. Physics in Medicine and Biology, 52(10):2865--2878, May 2007.
   

   @article{Vrtovec:pmb:07,
   
    author = "Vrtovec, T. and Ourselin, S. and Gomes, L. and Likar, B. and Pernus, F",
   
    title = {Automated generation of curved planar reformations from MR images of the spine},
   
    journal = {Physics in Medicine and Biology},
   
    year = "2007",
   
    volume ="52",
   
    number = "10",
   
    pages = "2865--2878",
   
    month = "May"
    
   }
   



8. D. Xiao, X.B. Gao, G.Y. Xiao, D.L. Li, W.S. Ng, and C.B. Tsang. Active contour model for internal sphincter boundary tracking in a sequence of ultrasound images. International Journal of Computer Assisted Radiology and Surgery, 2(Supp 1):S108-111, June 2007.
   

   @ARTICLE{DiXiao004,
   
    author = {D. Xiao and X.B. Gao and G.Y. Xiao and D.L. Li and W.S. Ng and C.B.
    Tsang},
   
    title = {Active contour model for internal sphincter boundary tracking in
    a sequence of ultrasound images},
   
    journal = {International Journal of Computer Assisted Radiology and Surgery},
   
    year = {2007},
   
    volume = {2},
   
    pages = {S108-111},
   
    number = {Supp 1},
   
    month = {June}
    
   }
   



9. D. Xiao, F. Liu, W. Shao, R.Y. Wu, P. Mohan, H. Ho , W.S. Ng, and C. Chen. A probe pulling system for prostate ultrasound image acquisition. International Journal of Computer Assisted Radiology and Surgery, 2(Supp 1):S134-S135, June 2007.
   

   @ARTICLE{DiXiao003,
   
    author = {D. Xiao and F. Liu and W. Shao and R.Y. Wu and P. Mohan and H. Ho
    and W.S. Ng and C. Chen},
   
    title = {A probe pulling system for prostate ultrasound image acquisition},
   
    journal = {International Journal of Computer Assisted Radiology and Surgery},
   
    year = {2007},
   
    volume = {2},
   
    pages = {S134-S135},
   
    number = {Supp 1},
   
    month = {June}
    
   }
   



10. D. Xiao, W.S. Ng, U.R. Abeyratne, and C.B.S. Tsang. A region and gradient based active contour model and its application in boundary tracking on anal canal ultrasound images. Pattern Recognition, 40(21):3522-3539, Dec 2007.
    

    @ARTICLE{DiXiao001,
    
     author = {D. Xiao and W.S. Ng and U.R. Abeyratne and C.B.S. Tsang},
    
     title = {A region and gradient based active contour model and its application
     in boundary tracking on anal canal ultrasound images},
    
     journal = {Pattern Recognition},
    
     year = {2007},
    
     volume = {40},
    
     pages = {3522-3539},
    
     number = {21},
    
     month = {Dec}
     
    }
    



11. J. Yelnik, E. Bardinet, D. Dormont, G. Malandain, S. Ourselin, D. Tandé, C. Karachi, N. Ayache, P. Cornu, and Y. Agid. A three-dimensional, histological and deformable atlas of the human basal ganglia. I. Atlas construction based on immunohistochemical and MRI data. Neuroimage, 34(2):618-638, Jan 2007.
    

    @Article{Yelnik:Neuroimage:07,
    
     author = "Yelnik, J. and Bardinet, E. and Dormont, D. and Malandain, G. and Ourselin, S. and Tand{\'e}, D. and Karachi, C. and Ayache, N. and Cornu, P. and Agid, Y.",
    
     title = {A three-dimensional, histological and deformable atlas of the human basal ganglia. I. Atlas construction based on immunohistochemical and MRI data},
    
     journal = "Neuroimage",
    
     year = "2007",
    
     volume = "34",
    
     number = "2",
    
     pages = "618-638",
    
     month = "Jan"
     
    }
    



12. H. de Visser, C.J. Adam, S. Crozier, and M.J. Pearcy. The role of quadratus lumborum asymmetry in the occurrence of lesions in the lumbar vertebrae of cricket fast bowlers. Medical Engineering and Physics, 29:877-885, 2007.
    

    @Article{deVisser:mep:07,
    author = {de Visser, H. and Adam, C.J. and Crozier, S. and Pearcy, M.J.},
    title = {The role of quadratus lumborum asymmetry in the occurrence of lesions in the lumbar vertebrae of cricket fast bowlers},
    journal = {Medical Engineering and Physics},
    volume = {29},
    year = {2007},
    pages = {877-885} 
    }
    



13. H. de Visser, C. Rowe, and M.J. Pearcy. Robotic Testing Facility for the Measurement of the Mechanics of Spinal Joints. Proc ImechE Part H: J Eng in Med, 221(3):221-227, 2007.
    

    @Article{deVisser:engmed:07,
    author = {de Visser, H. and Rowe, C. and Pearcy, M.J.},
    title = {Robotic Testing Facility for the Measurement of the Mechanics of Spinal Joints},
    journal = {Proc ImechE Part H: J Eng in Med},
    volume = {221},
    number = {3},
    year = {2007},
    pages = {221-227} 
    }
    

Conference articles

1. Oscar Acosta, Hans Frimmel, Aaron Fenster, and Sebastien Ourselin. Filtering and Restoration of Structures in 3D Ultrasound Images. In 2007 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Washington D.C. USA, pages 888-891, 12-15 April 2007 . IEEE.
   

   @InProceedings{Acosta:ISBI:07,
   
    Author = {Acosta, Oscar and Frimmel, Hans and Fenster, Aaron and Ourselin, Sebastien},
   
    Title = {Filtering and Restoration of Structures in 3{D} Ultrasound Images},
   
    BookTitle = {2007 IEEE International Symposium on Biomedical Imaging: From Nano to Macro},
   
    Address = {Washington D.C. USA},
   
    month = {12-15 April},
   
    optannote = {},
   
    optcrossref = {},
   
    opteditor = {},
   
    optkey = {},
   
    pages = {888-891},
   
    optnumber = {},
   
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    publisher = {IEEE},
   
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    pdf ={http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4193429&isnumber=4193197},
   
    year = 2007
    
   }
   



2. O. Comas, M. Cheng, Z. Taylor, and S. Ourselin. A new frontier for surgery simulation: implementing a GPU physical model with CUDA. In ICT Centre Conference 2007, Sydney, Australia , November 13-14 2007.
   

   @InProceedings{Comas2007ICT,
   
    author = {Comas, O. and Cheng, M. and Taylor, Z. and Ourselin, S.},
   
    title = {A new frontier for surgery simulation: implementing a {GPU} physical model with {CUDA}},
   
    booktitle = {ICT Centre Conference 2007},
   
    year = {2007},
   
    month = {November 13-14},
   
    address = {Sydney, Australia}
    
   }
   



3. T-M. Diep, P. Bourgeat, and S. Ourselin. Efficient Use of Cerebral Cortical Thickness to Correct Brain MR Segmentation. In IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Washington DC, USA, pages 592-595 , April 2007. IEEE.
   

   @InProceedings{Bourgeat:isbi:07,
   
    Author = {Diep, T-M. and Bourgeat, P. and Ourselin, S.},
   
    Title = {Efficient Use of Cerebral Cortical Thickness to Correct Brain MR Segmentation},
   
    booktitle = {IEEE International Symposium on Biomedical Imaging: From Nano to Macro},
   
    publisher = {IEEE},
   
    address = {Washington DC, USA},
   
    month = {April},
   
    year = 2007,
   
    pages = {592-595}
    
   }
   



4. V. Doré, L. Duong, F. Cheriet, and M. Cheriet. Towards Segmentation of Pedicles on Posteroanterior X-Ray Views of Scoliotic Patients. In Lecture Notes in Computer Science, Analysis and Recognition, Montreal, pages 1028--1039 , 2007. Springer Berlin - Heidelberg.
   

   @INPROCEEDINGS{Dore1,
   
    author={V. Dor{\'e} and L. Duong and F. Cheriet and M. Cheriet},
   
    title={Towards Segmentation of Pedicles on Posteroanterior X-Ray Views of Scoliotic Patients},
   
    booktitle={International Conference on Image Analysis and recognition: ICIAR2007},
   
    year=2007,
   
    address={Montreal},
   
    booktitle={Lecture Notes in Computer Science, Analysis and Recognition},
   
    publisher={Springer Berlin - Heidelberg},
   
    year=2007,
   
    pages={1028--1039}
    
   }
   



5. J. Dowling, B. Planitz, A. Maeder, J. Du, B. Pham, C. Boyd, S. Chen, A. Bradley, and S. Crozier. Visual Quality Assessment of Watermarked Medical Images. In Y Jiang and B. Sahiner, editors, Proceedings of SPIE Volume 6515: Image Perception, Observer Performance, and Technology Assessment, San Diego, volume 5615, pages pp. 65151L1-12 , 2007.
   

   @INPROCEEDINGS{2007SPIE,
   
    author = {Dowling, J. and Planitz, B. and Maeder, A. and Du, J. and Pham, B.
    and Boyd, C. and Chen, S. and Bradley, A. and Crozier, S.},
   
    title = {Visual Quality Assessment of Watermarked Medical Images},
   
    booktitle = {Proceedings of SPIE Volume 6515: Image Perception, Observer Performance,
    and Technology Assessment, San Diego},
   
    year = {2007},
   
    editor = {Jiang, Y and Sahiner, B.},
   
    volume = {5615},
   
    pages = {pp. 65151L1-12}
    
   }
   



6. L Ellis, N Dowson, J Matas, and R Bowden. Linear Predictors for Fast Simultaneous Modeling and Tracking. In Workshop on Non-rigid Registration and Tracking through Learning, IEEE 11th International Conference on Computer Vision, Rio de Janeiro, Brazil, pages 1--8, October 2007.
   

   @InProceedings{ellis07linear,
   
    author = {Ellis, L and Dowson, N and Matas, J and Bowden, R},
   
    title = {Linear Predictors for Fast Simultaneous Modeling and
    Tracking},
   
    OPTcrossref = {},
   
    OPTkey = {},
   
    booktitle = {Workshop on Non-rigid Registration and Tracking through
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    year = {2007},
   
    OPTeditor = {},
   
    OPTvolume = {},
   
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    address = {Rio de Janeiro, Brazil},
   
    month = {October},
   
    OPTorganization = {},
   
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    OPTnote = {},
   
    OPTannote = {}
    
   }
   



7. C. Forest, O. Comas, C. Vaysière, L. Soler, and J. Marescaux. Ultrasound and needle insertion simulators built on real patient-based data. In Studies in Health Technology and Informatics (MMVR 15), volume 125, Long Beach, California, USA , pages 136-139, February 6-9 2007. IOS Press.
   

   @InProceedings{Forest2007MMVR,
   
    author = {Forest, C. and Comas, O. and Vaysi\`ere, C. and Soler, L. and Marescaux, J.},
   
    title = {Ultrasound and needle insertion simulators built on real patient-based data},
   
    booktitle = {Studies in Health Technology and Informatics (MMVR 15)},
   
    pages = {136-139},
   
    volume = {125},
   
    publisher = {IOS Press},
   
    year = {2007},
   
    month = {February 6-9},
   
    address = {Long Beach, California, USA}
    
   }
   



8. H. Frimmel, O. Acosta, A. Fenster, and S. Ourselin. Reduction of attenuation effects in 3D transrectal ultrasound images. In SPIE Medical Imaging, 2007.
   

   @INPROCEEDINGS{frimmel0013,
   
    AUTHOR = {H.~Frimmel and O.~Acosta and A.~Fenster and S.~Ourselin},
   
    TITLE = {Reduction of attenuation effects in 3D transrectal ultrasound images},
   
    BOOKTITLE = {SPIE Medical Imaging},
   
    YEAR = {2007},
   
    VOLUME = {},
   
    NUMBER = {},
   
    PAGES = {},
   
    
   }
   



9. J. Fripp, P. Bourgeat, S. Crozier, and S. Ourselin. Shape-based segmentation of MRIs of the bones in the knee. In SPIE: Medical Imaging, volume 6512, San Diego, CA, USA, pages 651212, February 2007 . SPIE.
   

   @InProceedings{Fripp2007:SPIE,
   
    Title = {Shape-based segmentation of MRIs of the bones in the knee},
   
    Author = {J. Fripp and P. Bourgeat and S. Crozier and S. Ourselin},
   
    BookTitle = {SPIE: Medical Imaging},
   
    Volume = {6512},
   
    Pages = {651212},
   
    Address = {San Diego, CA, USA},
   
    Publisher = {SPIE},
   
    month = "February",
   
    opteditor = {Josien P. W. Pluim, Joseph M. Reinhardt},
   
    year = 2007
    
   }
   



10. J Fripp, S Crozier, S.K Warfield, and S. Ourselin. Automatic Segmentation of Articular Cartilage in Magnetic Resonance Images of the Knee. In 10th International Conference on Medical Image Computing and Computer Assisted Intervention, Brisbane, Australia, pages 186-194, October 2007.
    

    @InProceedings{Fripp:miccai:2007,
    
     Author = {Fripp, J and Crozier, S and Warfield, S.K and Ourselin, S.},
    
     Title = {Automatic Segmentation of Articular Cartilage in Magnetic Resonance Images of the Knee},
    
     BookTitle = {10th International Conference on Medical Image Computing and Computer Assisted Intervention},
    
     Year = {2007},
    
     pages = {186-194},
    
     Address = {Brisbane, Australia},
    
     Month = {October} 
     
    }
    



11. J. Fripp, S. Crozier, S.K. Warfield, and S. Ourselin. Automatic segmentation of the knee bones using 3D active shape models. In International Symposium on Biomedical Imaging: From Nano to Macro, Washington, pages 336-339, April 2007 . IEEE.
    

    @InProceedings{Fripp2007:ISBI,
    
     Title = {Automatic segmentation of the knee bones using 3D active shape models},
    
     Author = {J. Fripp and S. Crozier and S.K. Warfield and S. Ourselin},
    
     BookTitle = {International Symposium on Biomedical Imaging: From Nano to Macro},
    
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     Pages = {336-339},
    
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     Month = "April",
    
     opteditor = {},
    
     Year = 2007
     
    }
    



12. David Hellier, Josh Passenger, Mark N. Appleyard, and Sébastien Ourselin. Development of a new Colonoscopy Skills Trainer using Virtual Reality and Haptic Feedback. In SimTecT 2007 Healthcare Simulation Conference, pages 8 , 2007.
    

    @INPROCEEDINGS{Hellier2007a,
    
     author = {David Hellier and Josh Passenger and Mark N. Appleyard and S\'{e}bastien
     Ourselin},
    
     title = {Development of a new Colonoscopy Skills Trainer using Virtual Reality
     and Haptic Feedback},
    
     booktitle = {SimTecT 2007 Healthcare Simulation Conference},
    
     year = {2007},
    
     pages = {8}
     
    }
    



13. M. Holden, R. Moreno-Vallecillo, A. Harris, L. J. Gomes, T.-M. Diep, P. Bourgeat, and S. Ourselin. Expectation Maximization Classification and Laplacian-Based Thickness Measurement for Cerebral Cortex Thickness Estimation. In SPIE Medical Imaging, volume 6512, San Diego, California, pages 65120M, February 17-22 2007 .
    

    @InProceedings{Bourgeat:spie:07,
    
     Author = {Holden, M. and Moreno-Vallecillo, R. and Harris, A. and Gomes, L. J. 
     and Diep, T.-M. and Bourgeat, P. and Ourselin, S.},
    
     Title = {Expectation Maximization Classification and Laplacian-Based Thickness Measurement for Cerebral Cortex Thickness Estimation},
    
     BookTitle = {SPIE Medical Imaging},
    
     address = {San Diego, California},
    
     Volume = {6512},
    
     Pages = {65120M},
    
     month = {February 17-22},
    
     year = 2007
     
    }
    



14. Bhautik Joshi, Andriy Fedorov, Nikos Chrisochoides, Simon Warfield, and Sebastien Ourselin. Application-Driven Quantitative Assessment of Appraches to Mesh Generation. In 2007 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Washington DC, USA, pages 1160--1163 , April 2007. IEEE.
    

    @InProceedings{Joshi:ISBI:07,
    
     Author = {Bhautik Joshi and Andriy Fedorov and Nikos Chrisochoides and Simon Warfield and Sebastien Ourselin},
    
     Title = {Application-Driven Quantitative Assessment of Appraches to Mesh Generation},
    
     booktitle = {2007 IEEE International Symposium on Biomedical Imaging: From Nano to Macro},
    
     publisher = {IEEE},
    
     address = {Washington DC, USA},
    
     month = {April},
    
     year = 2007,
    
     pages = {1160--1163}
     
    }
    



15. H. Le, R. Li, J. Potter, and S. Ourselin. A Visual Dataflow Language for Biomedical Image Processing. In 2nd International Conference on Software and Data Technologies (ICSOFT 2007), Barcelona, Spain, pages 1160--1163 , July 22-25 2007.
    

    @InProceedings{Le:ICSOFT:07,
    
     Author = {Le, H. and Li, R. and Potter, J. and Ourselin, S.},
    
     Title = {A Visual Dataflow Language for Biomedical Image Processing},
    
     booktitle = {2nd International Conference on Software and Data Technologies (ICSOFT 2007)},
    
     address = {Barcelona, Spain},
    
     month = {July 22-25},
    
     year = 2007,
    
     pages = {1160--1163}
     
    }
    



16. Tanguy Le Fol, Oscar Acosta, Antoine Lucas, and Pascal Haigron. Angioplasty simulation using ChainMail method. In Proceedings of Spie: visualization, image-guided procedures and display, volume 6509, San Diego, USA, pages 65092X, February 2007 .
    

    @InProceedings{LeFolAcostaSPIE07,
    
     Author = {Le Fol, Tanguy and Acosta, Oscar and Lucas, Antoine and Haigron, Pascal},
    
     Title = {Angioplasty simulation using ChainMail method},
    
     BookTitle = {Proceedings of {S}pie: visualization, image-guided procedures and display},
    
     Volume = {6509},
    
     Number = {},
    
     Pages = {65092X},
    
     Address = {San Diego, USA},
    
     month = {February},
    
     pdf = {http://www.hal.inserm.fr/inserm-00153871/en/},
    
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17. P. Raniga, P. Bourgeat, V. Villemagne, G. O'Keefe, C. Rowe, and S. Ourselin. Automatic Cerebellar Grey Matter Extraction from PIB PET Images for SUVR Computation. In 13th Annual Meeting of the Organization for Human Brain Mapping, Chicago, IL, June 10-14 2007. Organization for Human Brain Mapping.
    Note: CD-ROM paper number 234 TH-PM .
    

    @INPROCEEDINGS{Raniga:ohbm:2007,
    
     AUTHOR = {Raniga, P. and Bourgeat, P. and Villemagne, V. and O'Keefe, G. and Rowe, C. and Ourselin, S.},
    
     TITLE = {Automatic Cerebellar Grey Matter Extraction from PIB PET Images for SUVR Computation},
    
     BOOKTITLE = {13th Annual Meeting of the Organization for Human Brain Mapping},
    
     YEAR = {2007},
    
     ADDRESS = {Chicago, IL},
    
     MONTH = {June 10-14},
    
     PUBLISHER = {Organization for Human Brain Mapping},
    
     NOTE = {CD-ROM paper number 234 TH-PM} 
     
    }
    



18. P. Raniga, P. Bourgeat, V. Villemagne, G. O'Keefe, C. Rowe, and S. Ourselin. PIB-PET Segmentation for Automatic SUVR Normalization Without MR Information. In Biomedical Imaging: From Nano to Macro, 2007. ISBI 2007. 4th IEEE International Symposium on, Washington DC, pages 348--351 , April 2007. IEEE.
    

    @InProceedings{Raniga:isbi:07,
    
     Author = {Raniga, P. and Bourgeat, P. and Villemagne, V. and O'Keefe, G. and Rowe, C. and Ourselin, S.},
    
     Title = {PIB-PET Segmentation for Automatic SUVR Normalization Without MR Information},
    
     BookTitle = {Biomedical Imaging: From Nano to Macro, 2007. ISBI 2007. 4th IEEE International Symposium on},
    
     Publisher = {IEEE},
    
     Address = {Washington DC},
    
     Month = {April},
    
     Year = {2007},
    
     Pages = {348--351}
     
    }
    



19. Parnesh Raniga, Pierrick Bourgeat, Victor Villemagne, Graeme O'Keefe, Christopher Rowe, and Sébastien Ourselin. Spline Based Inhomogeneity Correction for [11]C-PIB PET Segmentation Using Expectation Maximization. In Nicholas Ayache, Sébastien Ourselin, and Anthony Maeder, editors, Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2007, volume 4791 of LNCS, pages 228--235 , 2007. Springer.
    

    @inproceedings{Raniga:miccai:2007,
    
     editor = {Nicholas Ayache and S\'{e}bastien Ourselin and Anthony Maeder},
    
     booktitle = {Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2007},
    
     publisher = {Springer},
    
     location = {Heidelberg},
    
     series = {LNCS},
    
     volume = {4791},
    
     year = {2007},
    
     isbn = {978-3-540-75756-6},
    
     author = {Parnesh Raniga and Pierrick Bourgeat and Victor Villemagne and Graeme O'Keefe and Christopher Rowe and S\'{e}bastien Ourselin},
    
     title = {Spline Based Inhomogeneity Correction for [11]C-PIB PET Segmentation Using Expectation Maximization},
    
     pages = {228--235}
     
    }
    



20. O. Salvado. Parametrization of level-sets with B-splines. In ISBI'07, Arlington, VA, pages 1228-1231, 2007.

    Abstract:

    Level-sets are powerful techniques to segment images because they can accommodate any contour topologies. We used B-splines to model level-set functions using fewer knots/coefficients than pixels. This forces the contours to be smooth without the need to minimize smoothing terms. We implemented a standard variational method where objects were segmented based on their edges. We also developed a method to segment images of piecewise constant intensity objects. In this case the level-sets were directly computed from a classification step without evolving the contours. We tested our method on simulated MRI brain data. We showed that by using three level-sets in a multi-layer scheme, the classification of brain tissues was more robust than the standard fuzzy c-means algorithm even with spatial regularization.

    
    

    @INPROCEEDINGS{salvado_parametrization_2007,
    
     author = {O. Salvado},
    
     title = {Parametrization of level-sets with B-splines},
    
     booktitle = {ISBI'07},
    
     year = {2007},
    
     pages = {1228-1231},
    
     address = {Arlington, VA},
    
     abstract = {Level-sets are powerful techniques to segment images because they
     can accommodate any contour topologies. We used B-splines to model
     level-set functions using fewer knots/coefficients than pixels. This
     forces the contours to be smooth without the need to minimize smoothing
     terms. We implemented a standard variational method where objects
     were segmented based on their edges. We also developed a method to
     segment images of piecewise constant intensity objects. In this case
     the level-sets were directly computed from a classification step
     without evolving the contours. We tested our method on simulated
     MRI brain data. We showed that by using three level-sets in a multi-layer
     scheme, the classification of brain tissues was more robust than
     the standard fuzzy c-means algorithm even with spatial regularization.},
    
     journal = {4th IEEE International Symposium on Biomedical Imaging: From Nano
     to Macro},
    
     keywords = {contour topologies,image segmentation,level-sets,MRI brain data,multilayer
     scheme,parametrization,spatial regularization,standard fuzzy c-means
     algorithm,variational method}
     
    }
    



21. O. Salvado, P. Bourgeat, O. Acosta-Tamayo, and M. Zuluaga and S. Ourselin. Fuzzy classification of brain MRI using a priori knowledge: weighted fuzzy C-means. In MMBIA'07, Rio de Janeiro, October 2007. ICCV 2007.

    Abstract:

    We report in this communication a new formulation for the cost function of the well-known fuzzy C-means classification technique whereby we introduce weights. We derive the equations of this new weighted fuzzy C-means algorithm (WFCM) in the presence of additive and multiplicative bias field. We show that the weights can be designed in the same manner as prior probabilities commonly used in maximum a posteriori classifier (MAP) to introduce prior knowledge (e.g. using atlas), and increase robustness to noise (e.g. using Markov random field). Using prior probabilities of three popular MAP algorithms, we compare the performances of our proposed WFCM scheme using the simulated MRI T1W BrainWeb datasets, as well as five T1W MR patient scans. Our results show that WFCM achieves superior performances for low SNR conditions, whereas a Gaussian mixture model is desirable for high noise levels. WFCM allows rigorous comparison of fuzzy and probabilistic lassifiers, and offers a framework where improvements can be shared between those two types of classifier.

    
    

    @INPROCEEDINGS{salvado_fuzzy_2007,
    
     author = {O. Salvado and P. Bourgeat and O. Acosta-Tamayo and M. Zuluaga and
     S. Ourselin},
    
     title = {Fuzzy classification of brain MRI using a priori knowledge: weighted
     fuzzy C-means},
    
     booktitle = {MMBIA'07},
    
     year = {2007},
    
     address = {Rio de Janeiro},
    
     month = "October",
    
     publisher = {ICCV 2007},
    
     abstract = {We report in this communication a new formulation for the cost function
     of the well-known fuzzy C-means classification technique whereby
     we introduce weights. We derive the equations of this new weighted
     fuzzy C-means algorithm (WFCM) in the presence of additive and multiplicative
     bias field. We show that the weights can be designed in the same
     manner as prior probabilities commonly used in maximum a posteriori
     classifier (MAP) to introduce prior knowledge (e.g. using atlas),
     and increase robustness to noise (e.g. using Markov random field).
     Using prior probabilities of three popular MAP algorithms, we compare
     the performances of our proposed WFCM scheme using the simulated
     MRI T1W BrainWeb datasets, as well as five T1W MR patient scans.
     Our results show that WFCM achieves superior performances for low
     SNR conditions, whereas a Gaussian mixture model is desirable for
     high noise levels. WFCM allows rigorous comparison of fuzzy and probabilistic
     lassifiers, and offers a framework where improvements can be shared
     between those two types of classifier. },
    
     journal = {IEEE Computer Society Workshop on Mathematical Methods in Biomedical
     Image Analysis}
     
    }
    



22. O. Salvado, S. Yutszy, J. Derakshan, J. O. Heidenreich and S. Paul, M. Nguyen, I. Viohl, R. Hoffman, and J. Duerk and D.L. Wilson. Characterization of atherosclerosis lesions with trueFISP intravascular MRI. In ISMRM'07, Berlin, Germany, May 2007. ISMRM.
    

    @INPROCEEDINGS{salvado_characterization_2007,
    
     author = {O. Salvado and S. Yutszy and J. Derakshan and J. O. Heidenreich and
     S. Paul and M. Nguyen and I. Viohl and R. Hoffman and J. Duerk and
     D.L. Wilson},
    
     title = {Characterization of atherosclerosis lesions with trueFISP intravascular
     MRI},
    
     booktitle = {ISMRM'07},
    
     year = {2007},
    
     address = {Berlin, Germany},
    
     month = "May",
    
     publisher = {ISMRM},
    
     journal = {ISMRM conference of the International Society for Magnetic Resonance
     in Medicine}
     
    }
    



23. Z. Taylor, M. Cheng, and S. Ourselin. Real-time nonlinear finite element analysis for surgical simulation using graphics processing units. In Medical Image Computing and Computer-Assisted Intervention Conference 2007, volume 4791, pages 701, 2007. Springer.
    

    @INPROCEEDINGS{Taylor2007,
    
     author = {Z. Taylor and M. Cheng and S. Ourselin},
    
     title = {Real-time nonlinear finite element analysis for surgical simulation using graphics processing units},
    
     booktitle = {Medical Image Computing and Computer-Assisted Intervention Conference 2007},
    
     volume={4791},
    
     pages={701},
    
     year={2007},
    
     publisher={Springer},
    
     
    }
    



24. L. Zhou, R. Hartley, P. Lieby, N. Barnes, K. Anstey, N. Cherbuin, and P. Sachdev. A Study of Hippocampal Shape Difference Between Genders by Efficient Hypothesis Test and Discriminative Deformation. In Proceedings of International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI), pages 375--383, 2007.
    

    @inproceedings{zhou_MICCAI_2007,
    author = {Zhou, L. and Hartley, R. and Lieby, P. and Barnes, N. and Anstey, K. and Cherbuin, N. and Sachdev, P.},
    title = {A Study of Hippocampal Shape Difference Between Genders by Efficient Hypothesis Test and Discriminative Deformation},
    booktitle = {Proceedings of International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI)},
    address = {},
    month = {},
    year = {2007},
    pages = {375--383} 
    }
    

Miscellaneous

1. H. de Visser, J.P. Little, C.J. Adam, J.H. Evans, M.J. Pearcy, R. Labrom, and G. Askin. Patient specific parametric finite element models of scoliotic spines from CT scans.
   Note: In preparation, 2007.
   

   @unpublished{deVisser:unpub:07,
   author = {de Visser, H. and Little, J.P. and Adam, C.J. and Evans, J.H. and Pearcy, M.J. and Labrom, R. and Askin, G.},
   title = {Patient specific parametric finite element models of scoliotic spines from CT scans},
   year = {2007},
   note = {in preparation} 
   }