Abstract
Magnetic resonance imaging (MRI) is known as the gold standard for radiologists and clinicians for the diagnosis of different brain diseases. However, the images are often affected by low contrast which makes the interpretation and analysis difficult. In this paper, a novel image contrast enhancement method is proposed. The method relies on the decomposition of the image into squared eigenfunctions of the 2D Schrodinger operator. The decomposition depends on a parameter γ which controls the pixel intensity in the reconstruction. In addition, the method allows for filtering the noise simultaneously. The performance of the method is investigated on simulated and real images. The obtained results provide evidence for the feasibility and robustness of this method as a pre-processing tool for brain MRI images.
Original language | English (US) |
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Title of host publication | IEEE International Symposium on Biomedical Imaging, ISBI 2024 - Conference Proceedings |
Publisher | IEEE Computer Society |
ISBN (Electronic) | 9798350313338 |
DOIs | |
State | Published - 2024 |
Event | 21st IEEE International Symposium on Biomedical Imaging, ISBI 2024 - Athens, Greece Duration: May 27 2024 → May 30 2024 |
Publication series
Name | Proceedings - International Symposium on Biomedical Imaging |
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ISSN (Print) | 1945-7928 |
ISSN (Electronic) | 1945-8452 |
Conference
Conference | 21st IEEE International Symposium on Biomedical Imaging, ISBI 2024 |
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Country/Territory | Greece |
City | Athens |
Period | 05/27/24 → 05/30/24 |
Bibliographical note
Publisher Copyright:© 2024 IEEE.
Keywords
- Contrast enhancement
- MRI
- Semi-Classical Signal Analysis (SCSA) method
ASJC Scopus subject areas
- Biomedical Engineering
- Radiology Nuclear Medicine and imaging