Integrated Segmentation and Interpolation of Sparse Data

Adeline T M Paiement, M. Mirmehdi, Xianghua Xie, Mark C.K. Hamilton

Research output: Contribution to journalArticle (Academic Journal)peer-review

20 Citations (Scopus)


We address the two inherently related problems of segmentation and interpolation of 3D and 4D sparse data and propose a new method to integrate these stages in a level set framework. The interpolation process uses segmentation information rather than pixel intensities for increased robustness and accuracy. The method supports any spatial configurations of sets of 2D slices having arbitrary positions and orientations. We achieve this by introducing a new level set scheme based on the interpolation of the level set function by radial basis functions. The proposed method is validated quantitatively and/or subjectively on artificial data and MRI and CT scans and is compared against the traditional sequential approach, which interpolates the images first, using a state-of-the-art image interpolation method, and then segments the interpolated volume in 3D or 4D. In our experiments, the proposed framework yielded similar segmentation results to the sequential approach but provided a more robust and accurate interpolation. In particular, the interpolation was more satisfactory in cases of large gaps, due to the method taking into account the global shape of the object, and it recovered better topologies at the extremities of the shapes where the objects disappear from the image slices. As a result, the complete integrated framework provided more satisfactory shape reconstructions than the sequential approach.
Original languageEnglish
Pages (from-to)110-125
Number of pages16
JournalIEEE Transactions on Image Processing
Issue number1
Publication statusPublished - 1 Jan 2014

Structured keywords

  • CRICBristol


  • image reconstruction
  • image segmentation
  • interpolation
  • radial basis function networks
  • 2D slices
  • 3D sparse data
  • 4D sparse data
  • global shape
  • image interpolation method
  • integrated segmentation
  • level set function
  • radial basis function
  • shape reconstruction
  • sparse data interpolation
  • Deformable models
  • Image segmentation
  • Interpolation
  • Level set
  • Shape
  • Solid modeling
  • Three-dimensional displays
  • 3D/4D object modeling
  • RBF
  • level set methods
  • segmentation


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