Coil sensitivity map calculation using Biot-Savart Law at 3 tesla and parallel imaging in MRI


Tezin Türü: Doktora

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü, Türkiye

Tezin Onay Tarihi: 2017

Öğrenci: YUNUS EMRE ESİN

Danışman: FERDA NUR ALPASLAN

Özet:

Coil spatial sensitivity map is considered as one of the most valuable data used in parallel magnetic resonance imaging (MRI) reconstruction. In this study, a novel sensitivity map extraction method is introduced for phased-array coils. Proposed technique uses Biot-Savart law with coil shape information and low-resolution phase image data to form sensitivity maps. The performance of this method has been tested in the parallel image reconstruction task using sensitivity encoding technique. In MRI, coil sensitivity maps are complex-valued data that are typically represented with two components: phase and magnitude. In the proposed method, the phase information is retrieved from low-resolution central k-space signal data and the magnitude information is calculated using Biot-Savart law. Under the quasi-static assumption and using the duality principle, the spatial sensitivity maps of a head coil was computed for using parallel MRI reconstruction. In our experiments, volunteer and phantom scans were obtained using a 32-channel head coil and full field of view images were reconstructed using the proposed method. Experiments show that the resulting image qualities are higher than the ones obtained by the existing methods that use sensitivity maps calculated only from low-resolution image data. Moreover, several simulations were conducted using an electromagnetic simulation software tool to theoretically prove the success of the proposed technique. These simulation results indicate that the success of our method depends heavily on the size of the coil elements. Briefly, a new method for calculation of coil sensitivity is introduced which increases the image quality and homogeneity while reducing the artifacts.