Morphologic field morphing: Contour model-guided image interpolation
✍ Scribed by Wen-Shiang Vincent Shih; Wei-Chung Lin; Chin-Tu Chen
- Publisher
- John Wiley and Sons
- Year
- 1997
- Tongue
- English
- Weight
- 508 KB
- Volume
- 8
- Category
- Article
- ISSN
- 0899-9457
No coin nor oath required. For personal study only.
✦ Synopsis
An interpolation method using contours of organs as the logic field morphing, that uses the shape descriptions of the orcontrol parameters is proposed to recover the intensity information in gans in the source image slices to guide the recovery of the the physical gaps of serial cross-sectional images. In our method, intensity information in the physical gaps of serial cross-sectional contour models are used to generate the control lines required for medical images. In our method, the contour information derived the warping algorithm. Contour information derived from this contour from a contour model-guided image segmentation process is used model-based segmentation process is processed and used as the as the control parameters to perform image warping, which decontrol parameters to warp the corresponding regions in both input forms the corresponding regions on two source data slices into images into compatible shapes. In this way, the reliability of establishthe same shape. With corresponding organ regions in both data ing the correspondence among different segments of the same orslices being deformed into compatible shapes, the reliability to gans is improved and the intensity information for the interpolated intermediate slices can be derived more faithfully. To improve the locate different segments of the same organs is improved and the efficiency for calculating the image warp in the field morphing prointensity information for the interpolated intermediate slices can cess, a hierarchic decomposition process is proposed to localize the be filled in more faithfully. The remainder of this article is orgainfluence of each control line segment. In comparison with the existing nized as follows. In the next section, a survey of image interpolaintensity interpolation algorithms that only search for corresponding tion is provided. Then, the proposed interpolation method is depoints in a small physical neighborhood, this method provides more scribed. This is followed by the presentation of the experimental meaningful correspondence relationships by warping regions in imresults and a comparison with the existing whole-image intensity ages into similar shapes before resampling to account for significant interpolation methods. Finally, in Section V, the conclusions are shape differences. Several sets of experimental result are presented given.
to show that this method generates more realistic and less blurred interpolated images, especially when the shape difference of corresponding contours is significant.