Literature DB >> 34219859

A biological phantom for evaluation of CT image reconstruction algorithms.

J Cammin1, G S K Fung1, E K Fishman1, J H Siewerdsen2, J W Stayman2, K Taguchi1.   

Abstract

In recent years, iterative algorithms have become popular in diagnostic CT imaging to reduce noise or radiation dose to the patient. The non-linear nature of these algorithms leads to non-linearities in the imaging chain. However, the methods to assess the performance of CT imaging systems were developed assuming the linear process of filtered backprojection (FBP). Those methods may not be suitable any longer when applied to non-linear systems. In order to evaluate the imaging performance, a phantom is typically scanned and the image quality is measured using various indices. For reasons of practicality, cost, and durability, those phantoms often consist of simple water containers with uniform cylinder inserts. However, these phantoms do not represent the rich structure and patterns of real tissue accurately. As a result, the measured image quality or detectability performance for lesions may not reflect the performance on clinical images. The discrepancy between estimated and real performance may be even larger for iterative methods which sometimes produce "plastic-like", patchy images with homogeneous patterns. Consequently, more realistic phantoms should be used to assess the performance of iterative algorithms. We designed and constructed a biological phantom consisting of porcine organs and tissue that models a human abdomen, including liver lesions. We scanned the phantom on a clinical CT scanner and compared basic image quality indices between filtered backprojection and an iterative reconstruction algorithm.

Entities:  

Keywords:  biological phantom; computed tomography; edge sharpness; filtered backprojection; image quality; iterative reconstruction; liver lesions; noise power spectrum

Year:  2014        PMID: 34219859      PMCID: PMC8248767          DOI: 10.1117/12.2043714

Source DB:  PubMed          Journal:  Proc SPIE Int Soc Opt Eng        ISSN: 0277-786X


  7 in total

1.  Statistical image reconstruction for polyenergetic X-ray computed tomography.

Authors:  Idris A Elbakri; Jeffrey A Fessler
Journal:  IEEE Trans Med Imaging       Date:  2002-02       Impact factor: 10.048

2.  Assessment of an iterative reconstruction algorithm (SAFIRE) on image quality in pediatric cardiac CT datasets.

Authors:  B Kelly Han; Katharine L R Grant; Ross Garberich; Martin Sedlmair; Jana Lindberg; John R Lesser
Journal:  J Cardiovasc Comput Tomogr       Date:  2012-04-26

3.  Image quality and radiation dose of low dose coronary CT angiography in obese patients: sinogram affirmed iterative reconstruction versus filtered back projection.

Authors:  Rui Wang; U Joseph Schoepf; Runze Wu; Ryan P Reddy; Chuanchen Zhang; Wei Yu; Yi Liu; Zhaoqi Zhang
Journal:  Eur J Radiol       Date:  2012-05-10       Impact factor: 3.528

4.  Radiation dose reduction with Sinogram Affirmed Iterative Reconstruction technique for abdominal computed tomography.

Authors:  Mannudeep K Kalra; Mischa Woisetschläger; Nils Dahlström; Sarabjeet Singh; Maria Lindblom; Garry Choy; Petter Quick; Bernhard Schmidt; Martin Sedlmair; Michael A Blake; Anders Persson
Journal:  J Comput Assist Tomogr       Date:  2012 May-Jun       Impact factor: 1.826

5.  Prior image constrained compressed sensing (PICCS): a method to accurately reconstruct dynamic CT images from highly undersampled projection data sets.

Authors:  Guang-Hong Chen; Jie Tang; Shuai Leng
Journal:  Med Phys       Date:  2008-02       Impact factor: 4.071

6.  Low tube voltage intermediate tube current liver MDCT: sinogram-affirmed iterative reconstruction algorithm for detection of hypervascular hepatocellular carcinoma.

Authors:  M Hye Yu; Jeong Min Lee; Jeong-Hee Yoon; Jee Hyun Baek; Joon Koo Han; Byung-Ihn Choi; Thomas G Flohr
Journal:  AJR Am J Roentgenol       Date:  2013-07       Impact factor: 3.959

7.  Influence of sinogram affirmed iterative reconstruction of CT data on image noise characteristics and low-contrast detectability: an objective approach.

Authors:  Christian von Falck; Vesela Bratanova; Thomas Rodt; Bernhard Meyer; Stephan Waldeck; Frank Wacker; Hoen-oh Shin
Journal:  PLoS One       Date:  2013-02-13       Impact factor: 3.240

  7 in total

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