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Expectation-Maximization Optical Tomosynthetic Volume Imaging

Abstract Details

2008, Doctor of Philosophy (PhD), Wright State University, Engineering PhD.
Optical tomosynthetic imaging of 3-D objects from disparate 2-D images has been limited in the past by a lack of algorithmic enforcement of physical constraints, in particular within-scene obscuration and object self-occlusion. This paper presents a stochastic observation model of a tomosynthetic collection that explicitly includes an obscuration operator that is unknown by the sensor. The expectation-maximization algorithm is used to iteratively estimate the obscuration operator and to reconstruct the 3-D volume of interest. Explicit inclusion of obscuration effects greatly enhances the spatial and spectral accuracy of 3-D results without use of costly post-processing techniques. Performance metrics are introduced and the resultant receiver operating characteristics are presented.
Brian Rigling, PhD (Advisor)
Fred Garber, PhD (Committee Member)
Lang Hong, PhD (Committee Member)
Randolph Moses, PhD (Committee Member)
Michael Bryant, PhD (Committee Member)
43 p.

Recommended Citations

Citations

  • Hanna, P. M. (2008). Expectation-Maximization Optical Tomosynthetic Volume Imaging [Doctoral dissertation, Wright State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=wright1213216116

    APA Style (7th edition)

  • Hanna, Philip. Expectation-Maximization Optical Tomosynthetic Volume Imaging. 2008. Wright State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=wright1213216116.

    MLA Style (8th edition)

  • Hanna, Philip. "Expectation-Maximization Optical Tomosynthetic Volume Imaging." Doctoral dissertation, Wright State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=wright1213216116

    Chicago Manual of Style (17th edition)