Literature DB >> 16964851

An effective method to verify line and point spread functions measured in computed tomography.

Masaki Ohkubo1, Sinichi Wada, Toru Matsumoto, Kanae Nishizawa.   

Abstract

This study describes an effective method for verifying line spread function (LSF) and point spread function (PSF) measured in computed tomography (CT). The CT image of an assumed object function is known to be calculable using LSF or PSF based on a model for the spatial resolution in a linear imaging system. Therefore, the validities of LSF and PSF would be confirmed by comparing the computed images with the images obtained by scanning phantoms corresponding to the object function. Differences between computed and measured images will depend on the accuracy of the LSF and PSF used in the calculations. First, we measured LSF in our scanner, and derived the two-dimensional PSF in the scan plane from the LSE Second, we scanned the phantom including uniform cylindrical objects parallel to the long axis of a patient's body (z direction). Measured images of such a phantom were characterized according to the spatial resolution in the scan plane, and did not depend on the spatial resolution in the z direction. Third, images were calculated by two-dimensionally convolving the true object as a function of space with the PSF. As a result of comparing computed images with measured ones, good agreement was found and was demonstrated by image subtraction. As a criterion for evaluating quantitatively the overall differences of images, we defined the normalized standard deviation (SD) in the differences between computed and measured images. These normalized SDs were less than 5.0% (ranging from 1.3% to 4.8%) for three types of image reconstruction kernels and for various diameters of cylindrical objects, indicating the high accuracy of PSF and LSF that resulted in successful measurements. Further, we also obtained another LSF utilizing an inappropriate manner, and calculated the images as above. This time, the computed images did not agree with the measured ones. The normalized SDs were 6.0% or more (ranging from 6.0% to 13.8%), indicating the inaccuracy of the PSF and LSE We could verify LSFs and PSFs for three types of reconstruction kernels, and demonstrated differences between modulation transfer functions (MTFs) derived from validated LSFs and inaccurate LSFs. Our technique requires a simple phantom that is suitable for clinical scanning, and does not require a particular phantom containing some metals or specific fine structures, as required in methods previously used for measurements of spatial resolution. Therefore, the scanned image of the phantom will be reliable and of good quality, and this is used directly as a confident reference image for the verification. When one obtains LSF, PSF or MTF values, verification using our method is recommended. Further, when another method for the measurement of LSF and PSF is developed, it could be validated using our technique, as illustrated in the method proposed by Boone [Med. Phys. 28, 356-360 (2001)] and used in this paper.

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Year:  2006        PMID: 16964851     DOI: 10.1118/1.2214168

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  9 in total

1.  Application of CT-PSF-based computer-simulated lung nodules for evaluating the accuracy of computer-aided volumetry.

Authors:  Ayumu Funaki; Masaki Ohkubo; Shinichi Wada; Kohei Murao; Toru Matsumoto; Shinji Niizuma
Journal:  Radiol Phys Technol       Date:  2012-03-25

2.  Imaging of small spherical structures in CT: simulation study using measured point spread function.

Authors:  Masaki Ohkubo; Shinichi Wada; Masayuki Kunii; Toru Matsumoto; Kanae Nishizawa
Journal:  Med Biol Eng Comput       Date:  2007-11-10       Impact factor: 2.602

3.  Computer modeling of the spatial resolution properties of a dedicated breast CT system.

Authors:  Kai Yang; Alexander L C Kwan; John M Boone
Journal:  Med Phys       Date:  2007-06       Impact factor: 4.071

4.  A method for evaluating the performance of computer-aided detection of pulmonary nodules in lung cancer CT screening: detection limit for nodule size and density.

Authors:  Hajime Kobayashi; Masaki Ohkubo; Akihiro Narita; Janaka C Marasinghe; Kohei Murao; Toru Matsumoto; Shusuke Sone; Shinichi Wada
Journal:  Br J Radiol       Date:  2017-01-03       Impact factor: 3.039

5.  Theoretical Analysis of Novel Quasi-3D Microscopy of Cell Deformation.

Authors:  Jun Qiu; Andrew D Baik; X Lucas Lu; Elizabeth M C Hillman; Zhuo Zhuang; X Edward Guo
Journal:  Cell Mol Bioeng       Date:  2011-12-23       Impact factor: 2.321

6.  Observer-independent nodule-detectability index for low-dose lung cancer screening CT: a pilot study.

Authors:  Masaki Ohkubo; Shinichi Wada; Satoshi Kanai; Kazuhiro Ishikawa; Janaka C Marasinghe; Toru Matsumoto
Journal:  Radiol Phys Technol       Date:  2013-06-09

7.  Accurate determination of CT point-spread-function with high precision.

Authors:  Akihiro Kayugawa; Masaki Ohkubo; Shinichi Wada
Journal:  J Appl Clin Med Phys       Date:  2013-07-08       Impact factor: 2.102

8.  Accuracy of lung nodule density on HRCT: analysis by PSF-based image simulation.

Authors:  Ken Ohno; Masaki Ohkubo; Janaka C Marasinghe; Kohei Murao; Toru Matsumoto; Shinichi Wada
Journal:  J Appl Clin Med Phys       Date:  2012-11-08       Impact factor: 2.102

9.  An algorithm for automated modulation transfer function measurement using an edge of a PMMA phantom: Impact of field of view on spatial resolution of CT images.

Authors:  Choirul Anam; Toshioh Fujibuchi; Wahyu Setia Budi; Freddy Haryanto; Geoff Dougherty
Journal:  J Appl Clin Med Phys       Date:  2018-10-19       Impact factor: 2.102

  9 in total

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