Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/452511
Title: Design and Implementation of magnetic field gradient waveform for optimal sampling of Magnetic resonance imaging data
Researcher: Pavan Poojar
Guide(s): Sairam Geethanath
Keywords: Engineering
Engineering and Technology
Engineering Electrical and Electronic
University: Visvesvaraya Technological University, Belagavi
Completed Date: 2019
Abstract: Magnetic Resonance Imaging (MRI) is a well-established imaging modality, which provides soft tissue contrast at high resolution. It has therefore been extensively used in the diagnosis and/or prognosis of numerous pathological conditions without using harmful radiations. However, MR acquisition takes a long time as compared to other imaging modalities such as Computed Tomography (CT). To overcome this limitation, efforts have been made to use non-Cartesian based acquisition such as spiral, radial, rosette and so on to reduce the scan time. The goal of thisresearch work isto design and implement magnetic field gradient waveforms for optimal sampling of magnetic resonance imaging data. Developing new pulse sequencesand testing on the scanner requiresa lot of time and effort. This is the major challenge faced by the researchers as they are required to be familiar with vendor-specific programming languages. Pulseq-GPI is an open source framework which has been developed to provide a single platform for rapid prototyping of pulse sequences by integrating Pulseq with Graphical Programming Interface (GPI). Pulseq framework is used to design the pulse sequences and is written in MATLAB. GPI is written in Python and allows prototyping of MRI. The work demonstrates the use of Pulseq-GPI for three pulse sequences - gradient echo, Spin Echo (SE), and SE- Echo Planar Imaging (EPI). Pulseq-GPI was demonstrated on in vitro phantom and in vivo brain data. Rapid prOtotyping of 2D non-Cartesian K-space trajEcTories (ROCKET) aims to promote rapid development and testing of new MR methods for non-Cartesian based acquisition starting from pulse sequence design to image analysis. This was achieved by using Pulseq for pulse sequence design and GPI for image reconstruction and analysis. ROCKET was demonstrated on two 2D non-Cartesian k-space trajectories Free Induction Decay (FID) based radial and variable density spiral.
Pagination: xix,136
URI: http://hdl.handle.net/10603/452511
Appears in Departments:Dayananda Sagar College of Engineering

Files in This Item:
File Description SizeFormat 
01_title.pdfAttached File85.28 kBAdobe PDFView/Open
02_preliminary pages.pdf267.07 kBAdobe PDFView/Open
03_abstract.pdf16.87 kBAdobe PDFView/Open
04_table of contents.pdf21.9 kBAdobe PDFView/Open
05_list of illustrations.pdf68.05 kBAdobe PDFView/Open
06_list of tables.pdf26.47 kBAdobe PDFView/Open
07_chapter 1.pdf1.41 MBAdobe PDFView/Open
08_chapter 2.pdf62.56 kBAdobe PDFView/Open
09_chapter 3.pdf1.24 MBAdobe PDFView/Open
10_chapter 4.pdf1.41 MBAdobe PDFView/Open
11_chapter 5.pdf2.71 MBAdobe PDFView/Open
12_chapter 6.pdf635.05 kBAdobe PDFView/Open
13_chapter 7.pdf28.46 kBAdobe PDFView/Open
14_bibliography.pdf56.62 kBAdobe PDFView/Open
15_appendix.pdf21.72 kBAdobe PDFView/Open
80_recommendation.pdf28.46 kBAdobe PDFView/Open
Show full item record


Items in Shodhganga are licensed under Creative Commons Licence Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).

Altmetric Badge: