• DocumentCode
    241019
  • Title

    Content based modified reaction-diffusion equation for modeling tumor growth of low grade glioma

  • Author

    Elazab, Ahmed ; Qingmao Hu ; Fucang Jia ; Xiaodong Zhang

  • Author_Institution
    Res. Lab. for Med. Imaging & Digital Surg., Univ. Town of Shenzhen, Shenzhen, China
  • fYear
    2014
  • fDate
    11-13 Dec. 2014
  • Firstpage
    107
  • Lastpage
    110
  • Abstract
    This paper presents a content based modified reaction diffusion (RD) equation for modeling glioma growth. The reaction diffusion equation is modified by a weighted parameter that measures the white matter proportion in a small window. Given two MRI time-points scans of the same patient, the manually segmented tumor of the first scan is used as an initial seed to the proposed method while the second scan is used as the ground truth to measure the accuracy of the simulated results. For healthy tissues segmentation around the initial seed, spatial fuzzy C-means algorithm that accounts for neighborhood information of the image is used. As a proof of concept, the proposed method is tested on one low grade glioma case with 7 month difference between the two scans. The preliminary results of the modified RD equation show higher accuracy as compared with the standard RD equation.
  • Keywords
    biomedical MRI; feature extraction; fuzzy set theory; image segmentation; medical image processing; partial differential equations; physiological models; reaction-diffusion systems; tumours; MRI scan; content based modified RD equation; content based modified reaction-diffusion equation; ground truth; healthy tissue segmentation; initial seed; low grade glioma case; low grade glioma growth modeling; manual tumor segmentation; simulation accuracy; spatial fuzzy C-means algorithm; standard RD equation; time 7 month; tumor growth modeling; weighted parameter; white matter proportion measurement; Biological system modeling; Biomechanics; Equations; Image segmentation; Lead; Magnetic resonance imaging; Mathematical model; Reaction diffusion; glioma; spatial fuzzy c-means; tumor growth;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering Conference (CIBEC), 2014 Cairo International
  • Conference_Location
    Giza
  • ISSN
    2156-6097
  • Print_ISBN
    978-1-4799-4413-2
  • Type

    conf

  • DOI
    10.1109/CIBEC.2014.7020929
  • Filename
    7020929