Three-dimensional ionospheric tomography reconstruction using the model function approach in Tikhonov regularization

2016 ◽  
Vol 121 (12) ◽  
pp. 12,104-12,115 ◽  
Author(s):  
Sicheng Wang ◽  
Sixun Huang ◽  
Jie Xiang ◽  
Hanxian Fang ◽  
Jian Feng ◽  
...  
Keyword(s):  
Tikhonov Regularization ◽  
Three Dimensional ◽  
Function Approach ◽  
Model Function ◽  
Ionospheric Tomography ◽  
Tomography Reconstruction

Three-Dimensional Computed Tomography Reconstruction and Measurement of Nasal End Deformity in Complete Unilateral Cleft Lip and Palate

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Binqing Wang ◽  
Meng Xu ◽  
Ningbei Yin ◽  
Yongqian Wang ◽  
Tao Song
Keyword(s):  
Computed Tomography ◽  
Cleft Lip ◽  
Cleft Lip And Palate ◽  
Three Dimensional ◽  
Tomography Reconstruction ◽  
Computed Tomography Reconstruction

Three-dimensional computerized ionospheric tomography using volumetric constraints

Radio Science ◽  
1998 ◽  
Vol 33 (6) ◽  
pp. 1793-1805 ◽  
Author(s):  
Chaitali Biswas ◽  
Helen Na
Keyword(s):  
Three Dimensional ◽  
Ionospheric Tomography ◽  
Computerized Ionospheric Tomography

scholarly journals Three-dimensional computed tomography reconstruction for operative planning in robotic segmentectomy: a pilot study

2018 ◽  
Vol 10 (1) ◽  
pp. 196-201 ◽  
Author(s):  
Julien Le Moal ◽  
Christophe Peillon ◽  
Jean-Nicolas Dacher ◽  
Jean-Marc Baste
Keyword(s):  
Computed Tomography ◽  
Pilot Study ◽  
Three Dimensional ◽  
Operative Planning ◽  
Tomography Reconstruction ◽  
Computed Tomography Reconstruction

scholarly journals Global sensitivity analysis of parameter uncertainty in landscape evolution models

2018 ◽  
Vol 11 (12) ◽  
pp. 4873-4888 ◽  
Author(s):  
Christopher J. Skinner ◽  
Tom J. Coulthard ◽  
Wolfgang Schwanghart ◽  
Marco J. Van De Wiel ◽  
Greg Hancock
Keyword(s):  
Sensitivity Analysis ◽  
Objective Function ◽  
Landscape Evolution ◽  
Relative Sensitivity ◽  
Function Approach ◽  
Sensitivity Analyses ◽  
Model Parameters ◽  
Model Function ◽  
Sediment Yields ◽  
Statistical Measures

Abstract. The evaluation and verification of landscape evolution models (LEMs) has long been limited by a lack of suitable observational data and statistical measures which can fully capture the complexity of landscape changes. This lack of data limits the use of objective function based evaluation prolific in other modelling fields, and restricts the application of sensitivity analyses in the models and the consequent assessment of model uncertainties. To overcome this deficiency, a novel model function approach has been developed, with each model function representing an aspect of model behaviour, which allows for the application of sensitivity analyses. The model function approach is used to assess the relative sensitivity of the CAESAR-Lisflood LEM to a set of model parameters by applying the Morris method sensitivity analysis for two contrasting catchments. The test revealed that the model was most sensitive to the choice of the sediment transport formula for both catchments, and that each parameter influenced model behaviours differently, with model functions relating to internal geomorphic changes responding in a different way to those relating to the sediment yields from the catchment outlet. The model functions proved useful for providing a way of evaluating the sensitivity of LEMs in the absence of data and methods for an objective function approach.

Acardius anceps with neck cyst and cleft palate: Three dimensional skeletal computed tomography reconstruction with discussion of the literature

2019 ◽  
Vol 112 (2) ◽  
pp. 137-140
Author(s):  
Martin J. C. Gemert ◽  
Geert J. Streekstra ◽  
Frank P. H. A. Vandenbussche ◽  
Peter G. J. Nikkels ◽  
Jeroen P. H. M. Wijngaard
Keyword(s):  
Computed Tomography ◽  
Cleft Palate ◽  
Three Dimensional ◽  
Tomography Reconstruction ◽  
Computed Tomography Reconstruction

scholarly journals Novel nonlinear reconstruction method with grey-level quantisation units for electron tomography

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Norio Baba ◽  
Kenji Kaneko ◽  
Misuzu Baba
Keyword(s):  
Cross Section ◽  
Electron Tomography ◽  
Three Dimensional ◽  
Reconstruction Technique ◽  
Reconstruction Method ◽  
Back Projection ◽  
Grey Level ◽  
Discrete Processing ◽  
Structural Image ◽  
Tomography Reconstruction

AbstractWe report a new computed tomography reconstruction method, named quantisation units reconstruction technique (QURT), applicable to electron and other fields of tomography. Conventional electron tomography methods such as filtered back projection, weighted back projection, simultaneous iterative reconstructed technique, etc. suffer from the ‘missing wedge’ problem due to the limited tilt-angle range. QURT demonstrates improvements to solve this problem by recovering a structural image blurred due to the missing wedge and substantially reconstructs the structure even if the number of projection images is small. QURT reconstructs a cross-section image by arranging grey-level quantisation units (QU pieces) in three-dimensional image space via unique discrete processing. Its viability is confirmed by model simulations and experimental results. An important difference from recently developed methods such as discrete algebraic reconstruction technique (DART), total variation regularisation—DART, and compressed sensing is that prior knowledge of the conditions regarding the specimen or the expected cross-section image is not necessary.

Sign in / Sign up

Export Citation Format

Share Document