Literature DB >> 2740436

X-ray energy optimisation in computed microtomography.

P Spanne1.   

Abstract

Expressions describing the absorbed dose and the number of incident photons necessary for the detection of a contrasting detail in x-ray transmission CT imaging of a circular phantom are derived as functions of the linear attenuation coefficients of the materials comprising the object and the detail. A shell of a different material can be included to allow simulation of CT imaging of the skulls of small laboratory animals. The equations are used to estimate the optimum photon energy in x-ray transmission computed microtomography. The optimum energy depends on whether the number of incident photons or the absorbed dose at a point in the object is minimised. For a water object of 300 mm diameter the two optimisation criteria yield optimum photon energies differing by an order of magnitude.

Entities:  

Mesh:

Year:  1989        PMID: 2740436     DOI: 10.1088/0031-9155/34/6/004

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  4 in total

1.  Machine learned texture prior from full-dose CT database via multi-modality feature selection for Bayesian reconstruction of low-dose CT.

Authors:  Yongfeng Gao; Jiaxing Tan; Yongyi Shi; Hao Zhang; Siming Lu; Amit Gupta; Haifang Li; Michael Reiter; Zhengrong Liang
Journal:  IEEE Trans Med Imaging       Date:  2021-12-30       Impact factor: 11.037

2.  A Feasibility Study of Extracting Tissue Textures From a Previous Full-Dose CT Database as Prior Knowledge for Bayesian Reconstruction of Current Low-Dose CT Images.

Authors:  Yongfeng Gao; Zhengrong Liang; William Moore; Hao Zhang; Marc J Pomeroy; John A Ferretti; Thomas V Bilfinger; Jianhua Ma; Hongbing Lu
Journal:  IEEE Trans Med Imaging       Date:  2019-01-03       Impact factor: 10.048

Review 3.  In vivo small-animal imaging using micro-CT and digital subtraction angiography.

Authors:  C T Badea; M Drangova; D W Holdsworth; G A Johnson
Journal:  Phys Med Biol       Date:  2008-08-29       Impact factor: 3.609

4.  Computational 3D histological phenotyping of whole zebrafish by X-ray histotomography.

Authors:  Yifu Ding; Daniel J Vanselow; Maksim A Yakovlev; Spencer R Katz; Alex Y Lin; Darin P Clark; Phillip Vargas; Xuying Xin; Jean E Copper; Victor A Canfield; Khai C Ang; Yuxin Wang; Xianghui Xiao; Francesco De Carlo; Damian B van Rossum; Patrick La Riviere; Keith C Cheng
Journal:  Elife       Date:  2019-05-07       Impact factor: 8.140

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.