A sparsity-based iterative algorithm for reconstruction of micro-CT images from highly undersampled projection datasets obtained with a synchrotron X-ray source

2016 ◽  
Vol 87 (12) ◽  
pp. 123701 ◽  
Author(s):  
S. Ali Melli ◽  
Khan A. Wahid ◽  
Paul Babyn ◽  
David M. L. Cooper ◽  
Varun P. Gopi
Keyword(s):  
Iterative Algorithm ◽  
Ct Images ◽  
Micro Ct ◽  
X Ray

Automated segmentation of murine lung tumors in x-ray micro-CT images

2014 ◽  
Author(s):  
Joshua K. Y. Swee ◽  
Clare Sheridan ◽  
Elza de Bruin ◽  
Julian Downward ◽  
Francois Lassailly ◽  
...  
Keyword(s):  
Lung Tumors ◽  
Ct Images ◽  
Automated Segmentation ◽  
Micro Ct ◽  
Murine Lung ◽  
X Ray

scholarly journals Selection in a 3D microtomographic image the region with the highest quality

2019 ◽  
pp. 160-168 ◽  
Author(s):  
A S Kornilov ◽  
I V Safonov ◽  
A V Goncharova ◽  
I V Yakimchuk
Keyword(s):  
Flow Simulation ◽  
Visual Quality ◽  
Quality Measures ◽  
Ct Images ◽  
Ct Image ◽  
Micro Ct ◽  
X Ray ◽  
Image Slice ◽  
Selection Of

We present an algorithm for processing of X-ray microtomographic (micro-CT) images that allows automatic selection of a sub-volume having the best visual quality for further mathematical simulation, for example, flow simulation. Frequently, an investigated sample occupies only a part of a volumetric image or the sample can be into a holder; a part of the image can be cropped. For each 2D slice across the Z-axis of an image, the proposed method locates a region corresponding to the sample. We explored applications of several existing blind quality measures for an estimation of the visual quality of a micro-CT image slice. Some of these metrics can be applied to ranking the image regions according to their quality. Our method searches for a cubic area located inside regions belonging to the sample and providing the maximal sum of the quality measures of slices crossing the cube across the Z-axis. The proposed technique was tested on synthetic and real micro-CT images of rocks.

scholarly journals Analysis of X-ray Micro-CT Images Observed with Compacted Bentonite

2008 ◽  
Vol 28-1 (2) ◽  
pp. 1127-1127
Author(s):  
Satoshi TOMIOKA ◽  
Shusuke NISlYAMA ◽  
Tamotsu KOZAKI ◽  
Seichi SATO
Keyword(s):  
Ct Images ◽  
Micro Ct ◽  
X Ray ◽  
Compacted Bentonite

Image Calibration Techniques for Removing Cupping and Ring Artifacts in X-ray Micro-CT Images

2011 ◽  
Vol 27 (11) ◽  
pp. 93-101 ◽  
Author(s):  
Yeon-Jong Jung ◽  
Tae-Sup Yun ◽  
Kwang-Yeom Kim ◽  
Jin-Hyun Choo
Keyword(s):  
Ct Images ◽  
Micro Ct ◽  
X Ray ◽  
Calibration Techniques ◽  
Image Calibration

Segementation of X-Ray Microtomography Data of Porous Scaffold

2007 ◽  
Vol 330-332 ◽  
pp. 911-914
Author(s):  
Shuo Zou ◽  
Serena Best ◽  
William Bonfield
Keyword(s):  
Porous Scaffold ◽  
High Surface ◽  
Ct Images ◽  
Interface Problem ◽  
Phase System ◽  
Porous Scaffolds ◽  
Micro Ct ◽  
Contrast Transfer Function ◽  
Data Set ◽  
X Ray

Computerized X-ray micro tomography (micro CT) is a powerful technique for studying the structure and properties of porous scaffold. A variety of sample parameters can be studied using a single micro CT scan [1]. In general a segmented data set is a required for most quantitative analysis. However, segmentation of CT data can be difficult due to the artifacts in micro CT images such as blurred interfaces due to the machine contrast transfer function and the partial volume effect. Therefore the segmentation can be biased and prone to errors. Many methods have been developed to improve segmentation, however the interface problem has not been solved perfectly [2]. Porous scaffolds suffer from these effects because of their high surface to volume ratio and hence large interface. In this paper we discuss the interface problem in detail and demonstrate the effect of voxel size on the histograms of CT images of porous scaffold as well as a thresholding method based on 2 dimensional histogram is also presented. The potential of this method in more complicated scenarios such as 3-phase system is currently being investigated [3].

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