Impact of Using Different Four-Dimensional Computed Tomography Data Sets to Design Proton Treatment Plans for Distal Esophageal Cancer

2009 ◽  
Vol 73 (2) ◽  
pp. 601-609 ◽  
Author(s):  
Xiaoning Pan ◽  
Xiaodong Zhang ◽  
Yupeng Li ◽  
Radhe Mohan ◽  
Zhongxing Liao
Keyword(s):  
Computed Tomography ◽  
Esophageal Cancer ◽  
Data Sets ◽  
Proton Treatment ◽  
Treatment Plans ◽  
Tomography Data

scholarly journals Removing multiple outliers and single-crystal artefacts from X-ray diffraction computed tomography data

2015 ◽  
Vol 48 (6) ◽  
pp. 1943-1955 ◽  
Author(s):  
Antonios Vamvakeros ◽  
Simon D. M. Jacques ◽  
Marco Di Michiel ◽  
Vesna Middelkoop ◽  
Christopher K. Egan ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Single Crystal ◽  
Tomographic Reconstruction ◽  
Projection Data ◽  
Data Sets ◽  
Two Dimensional ◽  
X Ray Diffraction ◽  
X Ray ◽  
Diffraction Patterns ◽  
Tomography Data

This paper reports a simple but effective filtering approach to deal with single-crystal artefacts in X-ray diffraction computed tomography (XRD-CT). In XRD-CT, large crystallites can produce spots on top of the powder diffraction rings, which, after azimuthal integration and tomographic reconstruction, lead to line/streak artefacts in the tomograms. In the simple approach presented here, the polar transform is taken of collected two-dimensional diffraction patterns followed by directional median/mean filtering prior to integration. Reconstruction of one-dimensional diffraction projection data sets treated in such a way leads to a very significant improvement in reconstructed image quality for systems that exhibit powder spottiness arising from large crystallites. This approach is not computationally heavy which is an important consideration with big data sets such as is the case with XRD-CT. The method should have application to two-dimensional X-ray diffraction data in general where such spottiness arises.

scholarly journals Quantitative assessment of acetabular bone defects: A study of 50 computed tomography data sets

PLoS ONE ◽  
2019 ◽  
Vol 14 (10) ◽  
pp. e0222511 ◽  
Author(s):  
Ronja A. Schierjott ◽  
Georg Hettich ◽  
Heiko Graichen ◽  
Volkmar Jansson ◽  
Maximilian Rudert ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Quantitative Assessment ◽  
Bone Defects ◽  
Data Sets ◽  
Acetabular Bone ◽  
Acetabular Bone Defects ◽  
Tomography Data
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