Enter your keyword

2-s2.0-33745280084

[vc_empty_space][vc_empty_space]

Progressive multigrid V-cycle phase unwrapping for MRI phase images

Dewi D.E.O.a, Suksmono A.B.a, Mengko T.L.R.a

a Department of Electrical Engineering, Imaging and Image Processing Research Group, Institut Teknologi Bandung, Indonesia

[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]We propose a progressive method which improves the conventional Multigrid V-Cycle Phase Unwrapping (PU) scheme. The method is aimed to accommodate the need of early visualization in solving wrapping problem in phase image. In essence, this technique formulates the wrapped phase image in a Partial Differential Equation (PDE) and solves it by performing a rough global scale solution in the first grid of Multigrid structure and constructing the subsequent levels of detail utilizing the gradients of residual error in coarse and fine grids. The intermediate solution is then superposed to the previous solutions and displayed to the user gradually to get an improved solution. In this paper, we look into the feasibility of utilizing this approach to Magnetic Resonance Imaging (MRI) application. The proposed system is evaluated on simulated as well as actual MRI phase images and shows promising progressive improvement in estimating the unwrapped phase image over the conventional one. © 2005 IEEE.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]MRI phase image,Multigrid V-Cycles,Phase Unwrapping (PU),Progressive,Residual Error Gradients[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]MRI phase image,Multigrid V-Cycle,Phase Unwrapping,Progressive,Residual Error Gradients[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/HEALTH.2005.1500483[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]