<p>Magnetic Resonance Imaging is an established technology for both imaging and</p><p>functional studies in clinical and research environments. The field is still very</p><p>research intense. Two major research areas are acquisition time and signal quality.</p><p>The last decade has provided tools for more efficient possibilities of trading these</p><p>factors against each other through parallel imaging.</p><p>In this thesis one parallel imaging method, Sensitivity Encoding for fast</p><p>MRI (SENSE) is examined. An alternative solution CCASENSE is developed.</p><p>CCASENSE reduces the acquisition time by estimating the sensitivity maps required</p><p>for SENSE to work instead of running a reference scan. The estimation</p><p>process is done by Blind Source Separation through Canonical Correlation Analysis.</p><p>It is shown that CCASENSE appears to estimate the sensitivity maps better</p><p>than ICASENSE which is a similar algorithm.</p>
Identifer | oai:union.ndltd.org:UPSALLA/oai:DiVA.org:liu-7953 |
Date | January 2006 |
Creators | Brodin, Henrik |
Publisher | Linköping University, Department of Biomedical Engineering, Institutionen för medicinsk teknik |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, text |
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