JOURNAL ARTICLE

Feature-Based Non-rigid Registration of Serial Section Images by Blending Rigid Transformations

Abstract

In this paper, we describe feature-based nonrigid registration of histological serial section images. Our method represents non-rigid deformation by blending the rigid transformations estimated in the local region around a control point. This approach can efficiently represent nonrigid deformation with a smaller number of control points than conventional methods that interpolate displacement, such as free-form deformation (FFD). A feature-based approach is adopted to extract the control points and robustly estimate the local rigid transformation at each control point. By blending the rigid transformations, the displacement at each pixel is computed as a transformation field. The experimental results demonstrate that the proposed method is effective for achieving non-rigid registration efficiently and robustly for histological serial section images.

Keywords:
Feature (linguistics) Displacement (psychology) Rigid transformation Section (typography) Computer vision Point (geometry) Deformation (meteorology) Control point Transformation (genetics) Computer science Artificial intelligence Pixel Free-form deformation Displacement field Image registration Mathematics Image (mathematics) Geometry Finite element method Engineering Physics Structural engineering

Metrics

4
Cited By
0.38
FWCI (Field Weighted Citation Impact)
15
Refs
0.64
Citation Normalized Percentile
Is in top 1%
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Citation History

Topics

Medical Image Segmentation Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
AI in cancer detection
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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