Multimodal Medical Image Registration Based on an Information-Theory Measure with Histogram Estimation of Continuous Image Representation
Joint Authors
Coatrieux, Jean Louis
Shu, Huazhong
Liu, Zhoufeng
Li, Bicao
Yang, Guanyu
Source
Mathematical Problems in Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-04-29
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
This work presents a novel method for multimodal medical registration based on histogram estimation of continuous image representation.
The proposed method, regarded as “fast continuous histogram estimation,” employs continuous image representation to estimate the joint histogram of two images to be registered.
The Jensen–Arimoto (JA) divergence is a similarity measure to measure the statistical dependence between medical images from different modalities.
The estimated joint histogram is exploited to calculate the JA divergence in multimodal medical image registration.
In addition, to reduce the grid effect caused by the grid-aligning transformations between two images and improve the implementation speed of the registration method, random samples instead of all pixels are extracted from the images to be registered.
The goal of the registration is to optimize the JA divergence, which would be maximal when two misregistered images are perfectly aligned using the downhill simplex method, and thus to get the optimal geometric transformation.
Experiments are conducted on an affine registration of 2D and 3D medical images.
Results demonstrate the superior performance of the proposed method compared to standard histogram, Parzen window estimations, particle filter, and histogram estimation based on continuous image representation without random sampling.
American Psychological Association (APA)
Li, Bicao& Yang, Guanyu& Liu, Zhoufeng& Coatrieux, Jean Louis& Shu, Huazhong. 2018. Multimodal Medical Image Registration Based on an Information-Theory Measure with Histogram Estimation of Continuous Image Representation. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1206081
Modern Language Association (MLA)
Li, Bicao…[et al.]. Multimodal Medical Image Registration Based on an Information-Theory Measure with Histogram Estimation of Continuous Image Representation. Mathematical Problems in Engineering No. 2018 (2018), pp.1-12.
https://search.emarefa.net/detail/BIM-1206081
American Medical Association (AMA)
Li, Bicao& Yang, Guanyu& Liu, Zhoufeng& Coatrieux, Jean Louis& Shu, Huazhong. Multimodal Medical Image Registration Based on an Information-Theory Measure with Histogram Estimation of Continuous Image Representation. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1206081
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1206081