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You searched for subject:(maximum a posterior). Showing records 1 – 2 of 2 total matches.

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Southern Illinois University

1. Xu, Shiyu. TOMOGRAPHIC IMAGE RECONSTRUCTION: IMPLEMENTATION, OPTIMIZATION AND COMPARISON IN DIGITAL BREAST TOMOSYNTHESIS.

Degree: PhD, Electrical and Computer Engineering, 2014, Southern Illinois University

Conventional 2D mammography was the most effective approach to detecting early stage breast cancer in the past decades of years. Tomosynthetic breast imaging is a potentially more valuable 3D technique for breast cancer detection. The limitations of current tomosynthesis systems include a longer scanning time than a conventional digital X-ray modality and a low spatial resolution due to the movement of the single X-ray source. Dr.Otto Zhou's group proposed the concept of stationary digital breast tomosynthesis (s-DBT) using a Carbon Nano-Tube (CNT) based X-ray source array. Instead of mechanically moving a single X-ray tube, s-DBT applies a stationary X-ray source array, which generates X-ray beams from different view angles by electronically activating the individual source prepositioned at the corresponding view angle, therefore eliminating the focal spot motion blurring from sources. The scanning speed is determined only by the detector readout time and the number of sources regardless of the angular coverage spans, such that the blur from patient's motion can be reduced due to the quick scan. S-DBT is potentially a promising modality to improve the early breast cancer detection by providing decent image quality with fast scan and low radiation dose. DBT system acquires a limited number of noisy 2D projections over a limited angular range and then mathematically reconstructs a 3D breast. 3D reconstruction is faced with the challenges of cone-beam and flat-panel geometry, highly incomplete sampling and huge reconstructed volume. In this research, we investigated several representative reconstruction methods such as Filtered backprojection method (FBP), Simultaneous algebraic reconstruction technique (SART) and Maximum likelihood (ML). We also compared our proposed statistical iterative reconstruction (IR) with particular prior and computational technique to these representative methods. Of all available reconstruction methods in this research, our proposed statistical IR appears particularly promising since it provides the flexibility of accurate physical noise modeling and geometric system description. In the following chapters, we present multiple key techniques of statistical IR to tomosynthesis imaging data to demonstrate significant image quality improvement over conventional techniques. These techniques include the physical modeling with a local voxel-pair based prior with the flexibility in its parameters to fine-tune image quality, the pre-computed parameter κ incorporated with the prior to remove the data dependence and to achieve a predictable resolution property, an effective ray-driven technique to compute the forward and backprojection and an over-sampled ray-driven method to perform high resolution reconstruction with a practical region of interest (ROI) technique. In addition, to solve the estimation problem with a fast computation, we also present a semi-quantitative method to optimize the relaxation parameter in a relaxed order-subsets framework and an optimization transfer based algorithm… Advisors/Committee Members: Chen, Ying.

Subjects/Keywords: high resolution reconstruction; maximum a posterior; optimization transfer; stationary digital breast tomosynthesis; statistical iterative reconstruction

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Xu, S. (2014). TOMOGRAPHIC IMAGE RECONSTRUCTION: IMPLEMENTATION, OPTIMIZATION AND COMPARISON IN DIGITAL BREAST TOMOSYNTHESIS. (Doctoral Dissertation). Southern Illinois University. Retrieved from http://opensiuc.lib.siu.edu/dissertations/979

Chicago Manual of Style (16th Edition):

Xu, Shiyu. “TOMOGRAPHIC IMAGE RECONSTRUCTION: IMPLEMENTATION, OPTIMIZATION AND COMPARISON IN DIGITAL BREAST TOMOSYNTHESIS.” 2014. Doctoral Dissertation, Southern Illinois University. Accessed June 16, 2019. http://opensiuc.lib.siu.edu/dissertations/979.

MLA Handbook (7th Edition):

Xu, Shiyu. “TOMOGRAPHIC IMAGE RECONSTRUCTION: IMPLEMENTATION, OPTIMIZATION AND COMPARISON IN DIGITAL BREAST TOMOSYNTHESIS.” 2014. Web. 16 Jun 2019.

Vancouver:

Xu S. TOMOGRAPHIC IMAGE RECONSTRUCTION: IMPLEMENTATION, OPTIMIZATION AND COMPARISON IN DIGITAL BREAST TOMOSYNTHESIS. [Internet] [Doctoral dissertation]. Southern Illinois University; 2014. [cited 2019 Jun 16]. Available from: http://opensiuc.lib.siu.edu/dissertations/979.

Council of Science Editors:

Xu S. TOMOGRAPHIC IMAGE RECONSTRUCTION: IMPLEMENTATION, OPTIMIZATION AND COMPARISON IN DIGITAL BREAST TOMOSYNTHESIS. [Doctoral Dissertation]. Southern Illinois University; 2014. Available from: http://opensiuc.lib.siu.edu/dissertations/979


Rochester Institute of Technology

2. Fokoue, Ernest. An optimal experimental design perspective on redial basis function regression.

Degree: 2010, Rochester Institute of Technology

This paper provides a new look at radial basis function regression that reveals striking similarities with the traditional optimal experimental design framework. We show theoreti- cally and computationally that the so-called relevant vectors derived through the relevance vector machine (RVM) and corresponding to the centers of the radial basis function net- work, are very similar and often identical to the support points obtained through various optimal experimental design criteria like D-optimality. This allows us to provide a sta- tistical meaning to the relevant centers in the context of radial basis function regression, but also opens the door to a variety of ways of approach optimal experimental design in multivariate settings. Advisors/Committee Members: Not listed.

Subjects/Keywords: D-Optimality; Marginal Likelihood; Maximum a posterior (MAP); Radial basis function regression; Relevance vector machine; Sensor Selection

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Fokoue, E. (2010). An optimal experimental design perspective on redial basis function regression. (Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/6548

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Fokoue, Ernest. “An optimal experimental design perspective on redial basis function regression.” 2010. Thesis, Rochester Institute of Technology. Accessed June 16, 2019. https://scholarworks.rit.edu/theses/6548.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Fokoue, Ernest. “An optimal experimental design perspective on redial basis function regression.” 2010. Web. 16 Jun 2019.

Vancouver:

Fokoue E. An optimal experimental design perspective on redial basis function regression. [Internet] [Thesis]. Rochester Institute of Technology; 2010. [cited 2019 Jun 16]. Available from: https://scholarworks.rit.edu/theses/6548.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Fokoue E. An optimal experimental design perspective on redial basis function regression. [Thesis]. Rochester Institute of Technology; 2010. Available from: https://scholarworks.rit.edu/theses/6548

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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