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FAST FOURIER TRANSFORM USING PARALLEL PROCESSING FOR MEDICAL APPLICATIONS

Jagtap, Vinod
http://rave.ohiolink.edu/etdc/view?acc_num=akron1270678206

Abstract Details

2010, Master of Science in Engineering, University of Akron, Biomedical Engineering.
The Fourier Transform is a mathematical operation used widely in many fields. In medical imaging it is used for many applications such as image filtering, image reconstruction and image analysis. It is an important image processing tool which is used to decompose an image into its sine and cosine components. The output of the transformation represents the image in the frequency domain, while the input image is the spatial domain equivalent. In the frequency domain image, each point represents a particular frequency contained in the spatial domain image [8]. The objective of the research is to develop an algorithm for the Fast Fourier Transform so that it will compute the Fourier Transform much faster for input data with fixed length. The algorithm is developed in the c language and MATLAB. The goal of this research work basically revolves around the use of the Fourier Transform for reconstruction of an image in MRI and CT scan machines. As we know, when MRI machines take an image of the human body, the output is in the form of raw data. The Fourier Transform is used to reconstruct the image from this raw data. When the raw data size is relatively small, it takes moderate time to reconstruct an image. But, as the raw data size continue increasing, the time for processing the reconstruction increases as well. That triggers the quest for a faster way to compute the Fourier Transform. The Fast Fourier Transform is an efficient algorithm available since 1965 to calculate computationally intensive Fourier Transforms. Our goal in this entire work is to develop a strategy to compute the Fast Fourier Transform more efficiently and to reduce the time it takes for calculation. This mathematical transform makes reconstruction of images with larger data size practical.
Dale Mugler, Dr (Advisor)
Wolfgang Pelz, Dr (Advisor)
Daniel Sheffer, Dr (Committee Member)
89 p.
Biomedical Research; Engineering
Fast Fourier Transform; Parallel Processing; Medical Imaging

Recommended Citations

Citations

  • Jagtap, V. (2010). FAST FOURIER TRANSFORM USING PARALLEL PROCESSING FOR MEDICAL APPLICATIONS [Master's thesis, University of Akron]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=akron1270678206

    APA Style (7th edition)

  • Jagtap, Vinod. FAST FOURIER TRANSFORM USING PARALLEL PROCESSING FOR MEDICAL APPLICATIONS. 2010. University of Akron, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=akron1270678206.

    MLA Style (8th edition)

  • Jagtap, Vinod. "FAST FOURIER TRANSFORM USING PARALLEL PROCESSING FOR MEDICAL APPLICATIONS." Master's thesis, University of Akron, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=akron1270678206

    Chicago Manual of Style (17th edition)

akron1270678206
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© 2010, all rights reserved.
This open access ETD is published by University of Akron and OhioLINK.