Analysis of Partial K-Space reconstruction algorithms for Magnetic Resonance Imaging
| Autor: | S. D. Joshi, Sabah Bashir, Soft Shabir |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Image sampling
medicine.diagnostic_test Computer science business.industry Magnetic resonance spectroscopic imaging Magnetic resonance imaging k-space Real-time MRI Iterative reconstruction Compressed sensing Sampling (signal processing) medicine Computer vision Artificial intelligence business Algorithm |
| Zdroj: | 2014 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT). |
| Popis: | There are different imaging techniques which are being used for diagnosis of human body. Medical Resonance Imaging (MRI) technique provides information that differs from other imaging techniques, one of the major advantages is that it can characterize and discriminate among tissues using their physical and biochemical properties. The patient acceptability is high as it requires little patient preparation for the test. In this paper we analyze different algorithms of Partial K-Space reconstruction used in MRI. We also review the Compressive Sensing/Sampling approach of image reconstruction from partial K-Space data. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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