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Simplification of breast deformation modelling to support breast cancer treatment planning

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The exact delineation of tumour boundaries is of utmost importance in the planning of cancer therapy, either surgery or pre- or post-operative radiation treatment. In the case of breast cancer one of the most advanced modalities is magnetic resonance imaging (MRI). Although MRI scans provide wealth of information about the structure of a tumour and the surrounding tissues, the data obtained represent the patient in a prone position, with breast, in a coil while surgery is performed in a supine position, on lying breast. There is no doubt that a patient's breast in both positions has a different shape and that this influences the intra-breast relations. Our present preliminary study introduces a simple breast model developed from prone images. The model should be built rapidly and by a simple procedure, based only on essential structures, and the goal is to prove its usefulness in treatment planning.
Twórcy
  • Institute of Automatic Control, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland
autor
  • Institute of Automatic Control, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland
  • Dept. of Radiology, Maria Skodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice Branch, Gliwice, Poland
autor
  • IIIrd Dept. of Radiotherapy and Chemotherapy, Breast Cancer Unit, Maria Skodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice Branch, Gliwice, Poland
autor
  • Institute of Automatic Control, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland
Bibliografia
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  • [4] Han L, Hipwell J, Eiben B, Barratt D, Modat M, Ourselin S, et al. A nonlinear biomechanical model based registration method for aligning prone and supine MR breast images. IEEE Trans Med Imaging 2013;33(3):682–94. http://dx.doi.org/10.1109/TMI.2013.2294539.
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  • [6] Lee AW, Rajagopal V, Gamage TB, Doyle A, Nielsen P, Nash M. Breast lesion co-localisation between X-ray and MR images using finite element modelling. Med Image Anal 2013;17(8):1256–64. http://dx.doi.org/10.1016/j.media.2013.05.011.
  • [7] Pathmanathan P, Gavaghan D, Whiteley J, Chapman S, Brady J. Predicting tumor location by modeling the deformation of the breast. IEEE Trans Biomed Eng 2008;55 (10):2471–80. http://dx.doi.org/10.1109/TBME.2008.925714.
  • [8] Russo J, Russo I. Techniques and methodological approaches in breast cancer research. Springer; 2014. http://dx.doi.org/10.1007/978-1-4939-0718-2.
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Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-23aaf2ec-ff19-4b03-bd9d-3a67719b3570
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