Version 1
: Received: 21 June 2023 / Approved: 22 June 2023 / Online: 22 June 2023 (11:33:56 CEST)
How to cite:
Herguedas Alonso, A.E.; García-Suárez, V.M.; Fernández-Martínez, J.L. Compressed Sensing Techniques Applied to Medical Images Obtained With Magnetic Resonance. Preprints2023, 2023061605. https://doi.org/10.20944/preprints202306.1605.v1
Herguedas Alonso, A.E.; García-Suárez, V.M.; Fernández-Martínez, J.L. Compressed Sensing Techniques Applied to Medical Images Obtained With Magnetic Resonance. Preprints 2023, 2023061605. https://doi.org/10.20944/preprints202306.1605.v1
Herguedas Alonso, A.E.; García-Suárez, V.M.; Fernández-Martínez, J.L. Compressed Sensing Techniques Applied to Medical Images Obtained With Magnetic Resonance. Preprints2023, 2023061605. https://doi.org/10.20944/preprints202306.1605.v1
APA Style
Herguedas Alonso, A.E., García-Suárez, V.M., & Fernández-Martínez, J.L. (2023). Compressed Sensing Techniques Applied to Medical Images Obtained With Magnetic Resonance. Preprints. https://doi.org/10.20944/preprints202306.1605.v1
Chicago/Turabian Style
Herguedas Alonso, A.E., Víctor Manuel García-Suárez and Juan Luis Fernández-Martínez. 2023 "Compressed Sensing Techniques Applied to Medical Images Obtained With Magnetic Resonance" Preprints. https://doi.org/10.20944/preprints202306.1605.v1
Abstract
The fast and reliable processing of medical images is of paramount importance to adequately generate data to feed machine learning algorithms that can prevent and diagnose health issues. Here we benchmark different compressed sensing techniques applied to magnetic resonance imaging as a means to reduce the acquisition time spent in the collection of data and signals that form the image. We show that by using these techniques, it is possible to reduce the number of signals needed and, therefore, substantially decrease the time to acquire the measurements. To this end, we have considered and compared different algorithms: the Iterative Re-Weighted Least Squares, the Iterative Soft Thresholding Algorithm, the Iterative Hard Thresholding Algorithm, the Primal Dual Algorithm and the Log-Barrier Algorithm. We have implemented such algorithms in different analysis programs that have been used to perform the reconstruction of the images and found that the Iterative Soft Thresholding Algorithm gives the optimal results. We found that the images obtained with this algorithm have less quality than the original ones, but the quality is good enough to distinguish each body structure and detect any health problems.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
