Surface-based rigid registration using a global optimization algorithm for assessment of MRI knee cartilage thickness changes

•An approach for globally solving the 3D rigid registration problem is proposed.•The method was used for assessment for MRI knee cartilage thickness changes.•The method was evaluated on MR images from porcine knees and human knees.•Experimental results show the effectiveness of our approach. Registr...

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Vydáno v:Biomedical Signal Processing and Control Ročník 18; s. 303 - 316
Hlavní autoři: Guo, Changyong, Cheng, Yuanzhi, Guo, Haoyan, Wang, Jinke, Wang, Yadong, Tamura, Shinichi
Médium: Journal Article
Jazyk:angličtina
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Vydáno: Elsevier Ltd 01.04.2015
Elsevier BV
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ISSN:1746-8094
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Abstract •An approach for globally solving the 3D rigid registration problem is proposed.•The method was used for assessment for MRI knee cartilage thickness changes.•The method was evaluated on MR images from porcine knees and human knees.•Experimental results show the effectiveness of our approach. Registration methods have become an important tool in many medical applications. Existing methods require a good initial estimation (transformation) in order to find a global solution, i.e., if the initial estimation is far from the actual solution, incorrect solution or mismatching is very likely. In contrast, this paper presents a novel approach for globally solving the three dimensional (3D) rigid registration problem. The registration is grounded on a mathematical theory—Lipschitz optimization. It achieves a guaranteed global optimality with a rough initial estimation (e.g., even a random guess). Moreover, Munkres assignment algorithm is used to find the point correspondences. It applies the distance matrix to find an optimal correspondence. Our method is evaluated and demonstrated on MR images from porcine knees and human knees. Compared with state-of-the-art methods, the proposed technique is more robust, more accurate to perform point to point comparisons of knee cartilage thickness values for follow-up studies on the same subject.
AbstractList •An approach for globally solving the 3D rigid registration problem is proposed.•The method was used for assessment for MRI knee cartilage thickness changes.•The method was evaluated on MR images from porcine knees and human knees.•Experimental results show the effectiveness of our approach. Registration methods have become an important tool in many medical applications. Existing methods require a good initial estimation (transformation) in order to find a global solution, i.e., if the initial estimation is far from the actual solution, incorrect solution or mismatching is very likely. In contrast, this paper presents a novel approach for globally solving the three dimensional (3D) rigid registration problem. The registration is grounded on a mathematical theory—Lipschitz optimization. It achieves a guaranteed global optimality with a rough initial estimation (e.g., even a random guess). Moreover, Munkres assignment algorithm is used to find the point correspondences. It applies the distance matrix to find an optimal correspondence. Our method is evaluated and demonstrated on MR images from porcine knees and human knees. Compared with state-of-the-art methods, the proposed technique is more robust, more accurate to perform point to point comparisons of knee cartilage thickness values for follow-up studies on the same subject.
Author Guo, Haoyan
Tamura, Shinichi
Wang, Jinke
Wang, Yadong
Cheng, Yuanzhi
Guo, Changyong
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  givenname: Shinichi
  surname: Tamura
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  organization: Center for Advanced Medical Engineering and Informatics, Osaka University, Suita 565-0871, Japan
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Keywords Changes over time
Global optimization
Femoral cartilage
Cartilage segmentation
Registration
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Japanese
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Snippet •An approach for globally solving the 3D rigid registration problem is proposed.•The method was used for assessment for MRI knee cartilage thickness...
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SubjectTerms Cartilage segmentation
Changes over time
Femoral cartilage
Global optimization
Registration
Title Surface-based rigid registration using a global optimization algorithm for assessment of MRI knee cartilage thickness changes
URI https://dx.doi.org/10.1016/j.bspc.2015.02.007
https://cir.nii.ac.jp/crid/1871991018183560320
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