scholarly journals Visualization of the Trochlear Nerve in the Cistern with Use of High-Resolution Turbo Spin-Echo Multisection Motion-Sensitized Driven Equilibrium

2013 ◽  
Vol 34 (7) ◽  
pp. 1434-1437 ◽  
Author(s):  
M. Kanoto ◽  
Y. Toyoguchi ◽  
T. Hosoya ◽  
A. Oda ◽  
Y. Sugai
Keyword(s):  
High Resolution ◽  
Spin Echo ◽  
Turbo Spin Echo ◽  
Trochlear Nerve ◽  
Turbo Spin

High-resolution T2-weighted (T2W) oblique plane turbo spin-echo (TSE) MRI for rectal adenocarcinoma staging

2015 ◽  
Vol 39 (4) ◽  
pp. 627-631 ◽  
Author(s):  
Christian B. van der Pol ◽  
Wael M. Shabana ◽  
Matthew D. McInnes ◽  
Nicola Schieda
Keyword(s):  
High Resolution ◽  
Spin Echo ◽  
Rectal Adenocarcinoma ◽  
Turbo Spin Echo ◽  
Turbo Spin

High-Resolution Diffusion Imaging Using a Radial Turbo-Spin-Echo Sequence: Implementation, Eddy Current Compensation, and Self-Navigation

2000 ◽  
Vol 144 (2) ◽  
pp. 243-254 ◽  
Author(s):  
Markus H.J Seifert ◽  
Peter M Jakob ◽  
Vladimir Jellus ◽  
Axel Haase ◽  
Claudia Hillenbrand
Keyword(s):  
High Resolution ◽  
Eddy Current ◽  
Spin Echo ◽  
Diffusion Imaging ◽  
Turbo Spin Echo ◽  
Current Compensation ◽  
Turbo Spin ◽  
Spin Echo Sequence

scholarly journals Building a high-resolution in vivo minimum deformation average model of the human hippocampus

2017 ◽  
Author(s):  
Nina Jacobsen ◽  
Julie Broni Munk ◽  
Maciej Plocharski ◽  
Lasse Riis Østergaard ◽  
Lars Marstaller ◽  
...  
Keyword(s):  
High Resolution ◽  
Spin Echo ◽  
Turbo Spin Echo ◽  
Matching Algorithm ◽  
Turbo Spin ◽  
Human Hippocampus ◽  
Non Linear ◽  
Minimum Deformation ◽  
Contrast Matching

AbstractObjectiveMinimum deformation averaging (MDA) procedures exploit the information contained in inter-individual variations to generate high-resolution, high-contrast models through iterative model building. However, MDA models built from different image contrasts reside in disparate spaces and their complementary information cannot be utilized easily. The aim of this work was to develop an algorithm for the non-linear alignment of two MDA models with different contrasts to create a high-resolution in vivo model of the human hippocampus with a spatial resolution of 300 μm.MethodsA Turbo Spin Echo MDA model covering the hippocampus was contrast matched to a whole-brain MP2RAGE MDA model and aligned using cross-correlation and non-linear transformation. The contrast matching algorithm followed a global voxel location-based approach to estimate the relationship between intensity values of the two models. The performance of the algorithm was evaluated by comparing it to a non-linear registration obtained using mutual information without contrast matching. The complimentary information from both contrasts was then utilized in an automated hippocampal subfield segmentation pipeline.ResultsThe contrast of the Turbo Spin Echo MDA model could successfully be matched to the MP2RAGE MDA model. Registration using cross correlation provided more accurate alignment of the models compared to a mutual information based approach. The segmentation using ASHS resulted in hippocampal subfield delineations that resembled the tissue boundaries observed in the Turbo Spin Echo MDA model.ConclusionThe developed contrast matching algorithm facilitated the creation of a high-resolution multi-modal in vivo MDA model of the human hippocampus. This model can be used to improve algorithms for hippocampal subfield segmentation and could potentially support the early detection of neurodegenerative diseases.

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