Extended multi-flip-angle B1 mapping: A 3D mapping method for inhomogeneous B1 fields

Hans Weber; Dominik Paul; Dominik V. Elverfeldt; Jürgen Hennig; Maxim Zaitsev

doi:10.1002/cmr.b.20170

A fast B1-mapping method for the correction and normalization of magnetization transfer ratio maps at 3 T

NeuroImage ◽

10.1016/j.neuroimage.2009.11.054 ◽

2010 ◽

Vol 49 (4) ◽

pp. 3015-3026 ◽

Cited By ~ 52

Author(s):

Steffen Volz ◽

Ulrike Nöth ◽

Anna Rotarska-Jagiela ◽

Ralf Deichmann

Keyword(s):

Magnetization Transfer ◽

Mapping Method ◽

Magnetization Transfer Ratio ◽

Transfer Ratio ◽

B1 Mapping

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Fast B1 mapping based on interleaved-three-flip-angle (ITFA) excitation

Medical Physics ◽

10.1118/1.4824151 ◽

2013 ◽

Vol 40 (11) ◽

pp. 112301 ◽

Cited By ~ 1

Author(s):

Lae Hoon Kang ◽

Dong Eun Kim ◽

Soo Yeol Lee

Keyword(s):

Flip Angle ◽

B1 Mapping

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Efficient Planar Surface-Based 3D Mapping Method for Mobile Robots Using Stereo Vision

IEEE Access ◽

10.1109/access.2019.2920511 ◽

2019 ◽

Vol 7 ◽

pp. 73593-73601 ◽

Cited By ~ 1

Author(s):

Binghua Guo ◽

Hongyue Dai ◽

Zhonghua Li ◽

Wei Huang

Keyword(s):

Mobile Robots ◽

Stereo Vision ◽

Mapping Method ◽

3D Mapping ◽

Planar Surface

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Robust 2D Mapping Integrating with 3D Information for the Autonomous Mobile Robot Under Dynamic Environment

Electronics ◽

10.3390/electronics8121503 ◽

2019 ◽

Vol 8 (12) ◽

pp. 1503 ◽

Cited By ~ 1

Author(s):

Bin Zhang ◽

Masahide Kaneko ◽

Hun-ok Lim

Keyword(s):

Mobile Robot ◽

Moving Objects ◽

Three Dimensional ◽

Dynamic Environment ◽

Mapping Method ◽

Research Field ◽

Working Environment ◽

3D Mapping ◽

Occupancy Probability ◽

3D Information

In order to move around automatically, mobile robots usually need to recognize their working environment first. Simultaneous localization and mapping (SLAM) has become an important research field recently, by which the robot can generate a map while moving around. Both two-dimensional (2D) mapping and three-dimensional (3D) mapping methods have been developed greatly with high accuracy. However, 2D maps cannot reflect the space information of the environment and 3D mapping needs long processing time. Moreover, conventional SLAM methods based on grid maps take a long time to delete the moving objects from the map and are hard to delete the potential moving objects. In this paper, a 2D mapping method integrating with 3D information based on immobile area occupied grid maps is proposed. Objects in 3D space are recognized and their space information (e.g., shapes) and properties (moving objects or potential moving objects like people standing still) are projected to the 2D plane for updating the 2D map. By using the immobile area occupied grid map method, recognized still objects are reflected to the map quickly by updating the immobile area occupancy probability with a high coefficient. Meanwhile, recognized moving objects and potential moving objects are not used for updating the map. The unknown objects are reflected to the 2D map with a lower immobile area occupancy probability so that they can be deleted quickly once they are recognized as moving objects or start to move. The effectiveness of our method is proven by experiments of mapping under dynamic indoor environment using a mobile robot.

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Phase-3D mapping method developed from back-projection stereovision model for fringe projection profilometry

Optics Express ◽

10.1364/oe.25.001262 ◽

2017 ◽

Vol 25 (2) ◽

pp. 1262 ◽

Cited By ~ 20

Author(s):

Zewei Cai ◽

Xiaoli Liu ◽

Ameng Li ◽

Qijian Tang ◽

Xiang Peng ◽

...

Keyword(s):

Mapping Method ◽

Fringe Projection ◽

3D Mapping ◽

Back Projection ◽

Fringe Projection Profilometry

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Dynamic motion analysis of dart throwers motion visualized through computerized tomography and calculation of the axis of rotation

Journal of Hand Surgery (European Volume) ◽

10.1177/1753193413508709 ◽

2013 ◽

Vol 39 (4) ◽

pp. 364-372 ◽

Cited By ~ 21

Author(s):

Y. Edirisinghe ◽

J. M. Troupis ◽

M. Patel ◽

J. Smith ◽

M. Crossett

Keyword(s):

Three Dimensional ◽

Mapping Method ◽

Transverse Plane ◽

Imaging Method ◽

3D Mapping ◽

3D Reconstructions ◽

Dynamic Motion ◽

Axis Of Rotation ◽

Landmark Identification ◽

Varus Angulation

We used a dynamic three-dimensional (3D) mapping method to model the wrist in dynamic unrestricted dart throwers motion in three men and four women. With the aid of precision landmark identification, a 3D coordinate system was applied to the distal radius and the movement of the carpus was described. Subsequently, with dynamic 3D reconstructions and freedom to position the camera viewpoint anywhere in space, we observed the motion pathways of all carpal bones in dart throwers motion and calculated its axis of rotation. This was calculated to lie in 27° of anteversion from the coronal plane and 44° of varus angulation relative to the transverse plane. This technique is a safe and a feasible carpal imaging method to gain key information for decision making in future hand surgical and rehabilitative practices.

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Accurate 3D Mapping Algorithm for Flexible Antennas

International Journal of Antennas and Propagation ◽

10.1155/2018/3748623 ◽

2018 ◽

Vol 2018 ◽

pp. 1-12

Author(s):

Saed Asaly ◽

Boaz Ben-Moshe ◽

Nir Shvalb

Keyword(s):

High Gain ◽

Mapping Method ◽

Experimental Result ◽

3D Mapping ◽

Mapping Algorithm ◽

Flexible Antennas ◽

Antenna Surface ◽

Rf Antenna ◽

Flexible Antenna ◽

Satellite Dish

This work addresses the problem of performing an accurate 3D mapping of a flexible antenna surface. Consider a high-gain satellite flexible antenna; even a submillimeter change in the antenna surface may lead to a considerable loss in the antenna gain. Using a robotic subreflector, such changes can be compensated for. Yet, in order to perform such tuning, an accurate 3D mapping of the main antenna is required. This paper presents a general method for performing an accurate 3D mapping of marked surfaces such as satellite dish antennas. Motivated by the novel technology for nanosatellites with flexible high-gain antennas, we propose a new accurate mapping framework which requires a small-sized monocamera and known patterns on the antenna surface. The experimental result shows that the presented mapping method can detect changes up to 0.1-millimeter accuracy, while the camera is located 1 meter away from the dish, allowing an RF antenna optimization for Ka and Ku frequencies. Such optimization process can improve the gain of the flexible antennas and allow an adaptive beam shaping. The presented method is currently being implemented on a nanosatellite which is scheduled to be launched at the end of 2018.

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3D Mapping of Subsurface Cracks in Alumina Using FIB

MRS Proceedings ◽

10.1557/proc-649-q7.7 ◽

2000 ◽

Vol 649 ◽

Cited By ~ 3

Author(s):

B.J. Inkson ◽

H.Z. Wu ◽

T. Steer ◽

G. Möbus

Keyword(s):

Focused Ion Beam ◽

Ion Beam ◽

Mapping Method ◽

New Method ◽

3D Mapping ◽

Data Set ◽

Subsurface Cracks ◽

3D Data ◽

Indentation Site

ABSTRACTA new method has been developed to map cracks in 3D using focused ion beam (FIB) microscopy. Using the FIB, many parallel 2D slices are cut in the specimen. Imaging each 2D slice down several directions enables the 3D co-ordinates of features in the slice to be determined. Computer alignment and reconstruction of the 2D slices generates a 3D data set of the analysed zone. The 3D mapping method has been applied to the analysis of the cracks around an indentation site in a Al2O3-5vol.%SiC nanocomposite. This reveals the 3D location and morphology of radial and deep lateral cracks at the indent periphery, surface localised crack clusters, and a crack deficient zone close to the indent centre.

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3D resistivity mapping of airborne EM data

Geophysics ◽

10.1190/1.1635042 ◽

2003 ◽

Vol 68 (6) ◽

pp. 1896-1905 ◽

Cited By ~ 12

Author(s):

Zhiyi Zhang

Keyword(s):

Inverse Operator ◽

Quantitative Information ◽

Mapping Method ◽

Mapping Technique ◽

3D Mapping ◽

Linear System Of Equations ◽

Model Update ◽

Large Linear System ◽

Airborne Electromagnetic ◽

Airborne Em

A 3D resistivity mapping technique has been developed to provide fast estimates of resistivity distributions in airborne electromagnetic surveys. This proposed 3D mapping method consists of an approximate 3D linear inverse operator and a generalized subspace solver. The 3D inverse operator can be generated using any forward approximation that is linear in resistivity. The generalized subspace method is an alternative to the conjugate gradient method, and it reduces the original large linear system of equations to a much smaller but nonlinear one that is solved iteratively. The major benefit of using generalized subspace methods is that subspace vectors can be built based upon physical principles such as skin and investigation depths. Since the 3D mapping is a linear inverse problem, no iteration, and thus no forward modeling nor sensitivity updating, is needed. The 3D resistivity‐mapping technique can be used directly to estimate 3D resistivity distribution or to provide a model update during an intermediate iteration in a nonlinear 3D inversion. Synthetic and field data examples indicate that the 3D mapping can provide quantitative information about the resistivity and spatial distributions of the 3D targets.

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