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Feature-guided shape-based image interpolation.

Tong-Yee Lee·Chao-Hung Lin
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Abstract

A feature-guided image interpolation scheme is presented. It is an effective and improved, shape-based interpolation method used for interpolating image slices in medical applications. The proposed method integrates feature line-segments to guide the shape-based method for better shape interpolation. An automatic method for finding these line segments is given. The proposed feature-guided shape-based method can manage translation, rotation and scaling situations when the slices have similar shapes. It can also interpolate intermediate shapes when the successive slices do not have similar shapes. This method is experimentally evaluated using artificial and real two-dimensional and three-dimensional data. The proposed method generated satisfactory interpolated results in these experiments. We demonstrate the practicality, effectiveness and reproducibility of the proposed method for interpolating medical images.

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AlgorithmsAnatomy, Cross-SectionalComputer SimulationHumansImage EnhancementImaging, Three-DimensionalMolarPattern Recognition, AutomatedPhantoms, ImagingQuality ControlRadiographyReproducibility of ResultsSample SizeSensitivity and SpecificityComparative StudyEvaluation StudyJournal ArticleResearch Support, Non-U.S. Gov'tValidation Study

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Tong-Yee Lee, Chao-Hung Lin. 2002. Feature-guided shape-based image interpolation.. https://doi.org/10.1109/tmi.2002.806574

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