Compressive Sensing for Three-Dimensional Brain Magnetic Resonance Imaging

Selrina D’souza, H. Anitha, Karunakar Kotegar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Three dimensional (3D) Magnetic Resonance Imaging (MRI) reconstructions depend heavily on the imaging speed. Magnetic Resonance (MR) images consist of large volume of redundant and sparse data. Therefore, the need to reduce this data without degrading the image information. In Fourier Domain, sparse nature of MR images enables image reconstruction with fewer Fourier coefficients. Fourier Transform (FT) maps the image into the frequency domain using fixed and same size window throughout the analysis. In our paper, a method to perform compressive sensing for MR image is presented. Anisotropic filtering using Active Contour Modelling is performed to smoothen the image in order to preserve edge information. MR image is converted into Fourier Domain using Discrete Fourier Transform (DFT). l1 and l2 reconstruction algorithms are used to reconstruct the images using minimum coefficients that have maximum information.

Original languageEnglish
Title of host publicationRecent Trends in Image Processing and Pattern Recognition - 2nd International Conference, RTIP2R 2018, Revised Selected Papers
EditorsK.C. Santosh, Ravindra S. Hegadi
PublisherSpringer Verlag
Pages294-302
Number of pages9
ISBN (Print)9789811391835
DOIs
Publication statusPublished - 01-01-2019
Event2nd International Conference on Recent Trends in Image Processing and Pattern Recognition, RTIP2R 2018 - Solapur, India
Duration: 21-12-201822-12-2018

Publication series

NameCommunications in Computer and Information Science
Volume1036
ISSN (Print)1865-0929

Conference

Conference2nd International Conference on Recent Trends in Image Processing and Pattern Recognition, RTIP2R 2018
CountryIndia
CitySolapur
Period21-12-1822-12-18

Fingerprint

Compressive Sensing
Magnetic Resonance Image
Magnetic Resonance Imaging
Magnetic resonance
Brain
Three-dimensional
3D Imaging
Active Contours
Sparse Data
Discrete Fourier transform
Reconstruction Algorithm
Image Reconstruction
Fourier coefficients
Image reconstruction
Discrete Fourier transforms
Frequency Domain
Fourier transform
Fourier transforms
Filtering
Imaging

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Mathematics(all)

Cite this

D’souza, S., Anitha, H., & Kotegar, K. (2019). Compressive Sensing for Three-Dimensional Brain Magnetic Resonance Imaging. In K. C. Santosh, & R. S. Hegadi (Eds.), Recent Trends in Image Processing and Pattern Recognition - 2nd International Conference, RTIP2R 2018, Revised Selected Papers (pp. 294-302). (Communications in Computer and Information Science; Vol. 1036). Springer Verlag. https://doi.org/10.1007/978-981-13-9184-2_26
D’souza, Selrina ; Anitha, H. ; Kotegar, Karunakar. / Compressive Sensing for Three-Dimensional Brain Magnetic Resonance Imaging. Recent Trends in Image Processing and Pattern Recognition - 2nd International Conference, RTIP2R 2018, Revised Selected Papers. editor / K.C. Santosh ; Ravindra S. Hegadi. Springer Verlag, 2019. pp. 294-302 (Communications in Computer and Information Science).
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D’souza, S, Anitha, H & Kotegar, K 2019, Compressive Sensing for Three-Dimensional Brain Magnetic Resonance Imaging. in KC Santosh & RS Hegadi (eds), Recent Trends in Image Processing and Pattern Recognition - 2nd International Conference, RTIP2R 2018, Revised Selected Papers. Communications in Computer and Information Science, vol. 1036, Springer Verlag, pp. 294-302, 2nd International Conference on Recent Trends in Image Processing and Pattern Recognition, RTIP2R 2018, Solapur, India, 21-12-18. https://doi.org/10.1007/978-981-13-9184-2_26

Compressive Sensing for Three-Dimensional Brain Magnetic Resonance Imaging. / D’souza, Selrina; Anitha, H.; Kotegar, Karunakar.

Recent Trends in Image Processing and Pattern Recognition - 2nd International Conference, RTIP2R 2018, Revised Selected Papers. ed. / K.C. Santosh; Ravindra S. Hegadi. Springer Verlag, 2019. p. 294-302 (Communications in Computer and Information Science; Vol. 1036).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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D’souza S, Anitha H, Kotegar K. Compressive Sensing for Three-Dimensional Brain Magnetic Resonance Imaging. In Santosh KC, Hegadi RS, editors, Recent Trends in Image Processing and Pattern Recognition - 2nd International Conference, RTIP2R 2018, Revised Selected Papers. Springer Verlag. 2019. p. 294-302. (Communications in Computer and Information Science). https://doi.org/10.1007/978-981-13-9184-2_26