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    Motion and deformation estimation from medical imagery by modeling sub-structure interaction and constraints

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    Type
    Conference Paper
    Authors
    Sundaramoorthi, Ganesh cc
    Hong, Byungwoo
    Yezzi, Anthony J.
    KAUST Department
    Electrical Engineering Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Visual Computing Center (VCC)
    Date
    2012-09-13
    Online Publication Date
    2012-09-13
    Print Publication Date
    2013-01-21
    Permanent link to this record
    http://hdl.handle.net/10754/564610
    
    Metadata
    Show full item record
    Abstract
    This paper presents a novel medical image registration algorithm that explicitly models the physical constraints imposed by objects or sub-structures of objects that have differing material composition and border each other, which is the case in most medical registration applications. Typical medical image registration algorithms ignore these constraints and therefore are not physically viable, and to incorporate these constraints would require prior segmentation of the image into regions of differing material composition, which is a difficult problem in itself. We present a mathematical model and algorithm for incorporating these physical constraints into registration / motion and deformation estimation that does not require a segmentation of different material regions. Our algorithm is a joint estimation of different material regions and the motion/deformation within these regions. Therefore, the segmentation of different material regions is automatically provided in addition to the image registration satisfying the physical constraints. The algorithm identifies differing material regions (sub-structures or objects) as regions where the deformation has different characteristics. We demonstrate the effectiveness of our method on the analysis of cardiac MRI which includes the detection of the left ventricle boundary and its deformation. The experimental results indicate the potential of the algorithm as an assistant tool for the quantitative analysis of cardiac functions in the diagnosis of heart disease.
    Citation
    Sundaramoorthi, G., Hong, B.-W., & Yezzi, A. (2012). Motion and deformation estimation from medical imagery by modeling sub-structure interaction and constraints. Computational Modelling of Objects Represented in Images III, 221–227. doi:10.1201/b12753-40
    Publisher
    Informa UK Limited
    Journal
    Computational Modelling of Objects Represented in Images III
    Conference/Event name
    3rd International Symposium on Computational Modelling of Objects Represented in Images: Fundamentals, Methods and Applications, CompIMAGE 2012
    ISBN
    9780415621342
    DOI
    10.1201/b12753-40
    ae974a485f413a2113503eed53cd6c53
    10.1201/b12753-40
    Scopus Count
    Collections
    Conference Papers; Electrical and Computer Engineering Program; Visual Computing Center (VCC); Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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