Reconstruction of serially acquired slices using physics-based modeling
This paper presents an accurate, computationally efficient, fast, and fully automated algorithm for the alignment of two-dimensional (2-D) serially acquired sections forming a 3-D volume. The approach relies on the determination of interslice correspondences. The features used for correspondence are...
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Published in | IEEE transactions on information technology in biomedicine Vol. 7; no. 4; pp. 394 - 403 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
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United States
IEEE
01.12.2003
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Subjects | |
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Abstract | This paper presents an accurate, computationally efficient, fast, and fully automated algorithm for the alignment of two-dimensional (2-D) serially acquired sections forming a 3-D volume. The approach relies on the determination of interslice correspondences. The features used for correspondence are extracted by a 2-D physics-based deformable model parameterizing the object shape. Correspondence affinities and global constrains render the method efficient and reliable. The method accounts for one of the major shortcomings of 2-D slices alignment of a 3-D volume, namely variable and nonuniform thickness of the slices. Moreover, no particular alignment direction is privileged, avoiding global offsets, biases, and error propagation. The method was evaluated on real images and the experimental results demonstrated its accuracy, as reconstruction errors were smaller than I degree in rotation and smaller than 1 pixel in translation. |
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AbstractList | This paper presents an accurate, computationally efficient, fast, and fully automated algorithm for the alignment of two-dimensional (2-D) serially acquired sections forming a 3-D volume. The approach relies on the determination of interslice correspondences. The features used for correspondence are extracted by a 2-D physics-based deformable model parameterizing the object shape. Correspondence affinities and global constrains render the method efficient and reliable. The method accounts for one of the major shortcomings of 2-D slices alignment of a 3-D volume, namely variable and nonuniform thickness of the slices. Moreover, no particular alignment direction is privileged, avoiding global offsets, biases, and error propagation. The method was evaluated on real images and the experimental results demonstrated its accuracy, as reconstruction errors were smaller than I degree in rotation and smaller than 1 pixel in translation. This paper presents an accurate, computationally efficient, fast, and fully automated algorithm for the alignment of two-dimensional (2-D) serially acquired sections forming a 3-D volume. The approach relies on the determination of interslice correspondences. The features used for correspondence are extracted by a 2-D physics-based deformable model parameterizing the object shape. Correspondence affinities and global constrains render the method efficient and reliable. The method accounts for one of the major shortcomings of 2-D slices alignment of a 3-D volume, namely variable and nonuniform thickness of the slices. Moreover, no particular alignment direction is privileged, avoiding global offsets, biases, and error propagation. The method was evaluated on real images and the experimental results demonstrated its accuracy, as reconstruction errors were smaller than 1 degree in rotation and smaller than 1 pixel in translation. |
Author | Pitas, I. Krinidis, S. Nikou, C. |
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BackLink | https://www.ncbi.nlm.nih.gov/pubmed/15000365$$D View this record in MEDLINE/PubMed |
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SubjectTerms | Algorithms Anatomy, Cross-Sectional - methods Biomedical imaging Computed tomography Cross-Sectional Studies Deformable models Finite element methods Humans Image Enhancement Image Interpretation, Computer-Assisted - methods Image reconstruction Image registration Imaging, Three-Dimensional - methods Models, Biological Physics - methods Physics computing Pixel Reproducibility of Results Sensitivity and Specificity Shape Subtraction Technique Two dimensional displays |
Title | Reconstruction of serially acquired slices using physics-based modeling |
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