Doctoral Thesis: Acquisition and reconstruction methods for magnetic resonance imaging


Event Speaker: 

Itthi Chatnuntawech

Event Location: 


Event Date/Time: 

Friday, December 4, 2015 - 12:00pm


Magnetic Resonance Imaging (MRI) is a non-invasive medical imaging modality used in radiology that has a wide range of applications in both diagnostic clinical imaging and medical research. MRI has progressively gained in importance in clinical use because of its ability to produce high quality images of soft tissue throughout the body without subjecting the patient to any ionizing radiation. In addition to exquisite anatomical detail obtained from the conventional MRI, the complementary physiological information is also available through the emerging specialized applications of MRI such as magnetic resonance spectroscopic imaging, quantitative susceptibility mapping, functional MRI, and diffusion MRI.

Despite its great versatility, MRI is limited by the time required to collect all necessary information. Since a typical MRI protocol consists of multiple scans of the same patient, the total scan time is commonly extended beyond half an hour. During the session, the patient must remain perfectly still within a tight and closed environment, raising difficulties for certain populations such as children and patients with claustrophobia. The long acquisition time of MRI not only reduces the availability of the MRI scanner, but also results in patient discomfort that could lead to a patient motion which degrades image quality. Therefore, reducing the acquisition time of MRI is a well-motivated problem.

This thesis proposes acquisition and reconstruction methods that aim to increase the imaging efficiency of MRI and two of its emerging specialized applications, magnetic resonance spectroscopic imaging and quantitative susceptibility mapping. In particular, each of the proposed methods increases the imaging efficiency by achieving at least one of two aims: reduction of total scan time and improved image quality by mitigating image artifacts, while minimizing reconstruction time.

Thesis supervisor: Prof. Elfar Adalsteinsson

Thesis committee: Prof. Kawin Setsompop, Prof. Jacob K White