Orientation adaptive fast marching method for contour tracking of small intestine

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Orientation adaptive fast marching method for contour tracking of small intestine

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The orientation of the small intestine varies among frames of a cinematic-magnetic resonance imaging (cine-MRI) sequence owing to small intestine peristalsis, which increases the complexity of its contour tracking. There are also leakage problems owing to the presence of low contrast areas in some frames. An improved fast marching method using an anisotropic Gaussian filter and a boundary penalty is presented for the contour tracking of small intestine segments. Experimental results show that the proposed method can track accurate contours of small intestine segments without leakage problems.

Inspec keywords: biomedical MRI; image matching; filtering theory; image segmentation

Other keywords: cinematic-magnetic resonance imaging sequence; small intestine; boundary penalty; contour tracking; orientation adaptive fast marching method; anisotropic Gaussian filter; cine-MRI sequence

Subjects: Medical magnetic resonance imaging and spectroscopy; Biomedical magnetic resonance imaging and spectroscopy; Optical, image and video signal processing; Biology and medical computing; Computer vision and image processing techniques; Patient diagnostic methods and instrumentation; Biomagnetism; Filtering methods in signal processing

References

    1. 1)
      • D. Ververidis , C. Kotropoulos . Gaussian mixture modeling by exploiting the Mahalanobis distance. IEEE Trans. Signal Process , 7 , 2797 - 2811
    2. 2)
    3. 3)
      • D.A. Forsyth , J. Ponce . (2002) Computer vision: a modern approach.
    4. 4)
      • Wang, W., Gao, J., Li, K.: `Structure-adaptive anisotropic filter with local structure tensors', Proc. Int. Symp. on Intelligent Information Technology Application, 2008, p. 1005–1010.
    5. 5)
      • J.A. Sethian . (1999) Level set methods and fast marching methods.
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