Spatiotemporal Free-Form Registration Method Assisted by a Minimum Spanning Tree During Discontinuous Transformations.

The sliding motion along the boundaries of discontinuous regions has been actively studied in B-spline free-form deformation framework. This study focusses on the sliding motion for a velocity field-based 3D+t registration. The discontinuity of the tangent direction guides the deformation of the obj...

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Publicado en:Journal of Digital Imaging Vol. 34; no. 1; pp. 190 - 204
Autores principales: Bae, Jang Pyo, Yoon, Siyeop, Vania, Malinda, Lee, Deukhee
Formato: diagnostic images equations & formulas tables/charts Journal Article
Publicado: Springer Nature Feb2021
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Feb2021
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      pub: Springer Nature
      place: New York, New York
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        atl: Spatiotemporal Free-Form Registration Method Assisted by a Minimum Spanning Tree During Discontinuous Transformations.
      aug:
        au:
          Bae, Jang Pyo
          Yoon, Siyeop
          Vania, Malinda
          Lee, Deukhee
        affil: Center for Healthcare Robotics, Korea Institute of Science and Technology, 5, Hwarang-ro 14-gil, 02792, Seoul, Seongbuk-gu, Korea
      sug:
        subj:
          Spatial Perception
          Tomography, X-Ray Computed
          Movement Physiology
          Geographic Factors
          Cardiovascular System Ultrasonography
          Printing, Three-Dimensional
          Electrotherapy
      ab: The sliding motion along the boundaries of discontinuous regions has been actively studied in B-spline free-form deformation framework. This study focusses on the sliding motion for a velocity field-based 3D+t registration. The discontinuity of the tangent direction guides the deformation of the object region, and a separate control of two regions provides a better registration accuracy. The sliding motion under the velocity field-based transformation is conducted under the α -Rényi entropy estimator using a minimum spanning tree (MST) topology. Moreover, a new topology changing method of the MST is proposed. The topology change is performed as follows: inserting random noise, constructing the MST, and removing random noise while preserving a local connection consistency of the MST. This random noise process (RNP) prevents the α -Rényi entropy-based registration from degrading in sliding motion, because the RNP creates a small disturbance around special locations. Experiments were performed using two publicly available datasets: the DIR-Lab dataset, which consists of 4D pulmonary computed tomography (CT) images, and a benchmarking framework dataset for cardiac 3D ultrasound. For the 4D pulmonary CT images, RNP produced a significantly improved result for the original MST with sliding motion (p<0.05). For the cardiac 3D ultrasound dataset, only a discontinuity-based registration indicated activity of the RNP. In contrast, the single MST without sliding motion did not show any improvement. These experiments proved the effectiveness of the RNP for sliding motion.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        equations & formulas
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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