Investigation of image noise in cone-beam CT imaging due to photon counting statistics with the Feldkamp algorithm by computer simulations

Cone beam CT (CBCT) imaging technique has found many applications in medical imaging in recent years since it provides three-dimensional image reconstruction with low contrast detectability and high resolution. In CBCT systems, image noise caused by photon counting statistics plays an important role in image quality by affecting low contrast detection and patient dose. In this paper, we studied image noise caused by photon counting statistics with the Feldkamp's cone beam reconstruction algorithm. A noise model based on photon counting detector was developed to provide the noise distribution in 3D image space and the quantitative relationships between image noise level and various CT parameters, including the exposure level, the number of projections, the reconstruction filter and the detector pixel size. Computer simulations of a spherical water phantom were conducted to test the theoretical model. This work provides the noise spatial distribution in cone-beam CT and its relationship with CBCT parameters. It can also provide local noise information for adaptive de-noising in the future.

[1]  Yong Yu,et al.  Flat panel detector-based cone beam CT lung imaging: preliminary system evaluation , 2005, SPIE Medical Imaging.

[2]  J C Gore,et al.  STATISTICAL LIMITATIONS IN COMPUTED TOMOGRAPHY , 1978 .

[3]  J. Wong,et al.  Flat-panel cone-beam computed tomography for image-guided radiation therapy. , 2002, International journal of radiation oncology, biology, physics.

[4]  M F Kijewski,et al.  The noise power spectrum of CT images. , 1987, Physics in medicine and biology.

[5]  H. E. Johns,et al.  Physics of Radiology , 1983 .

[6]  Aruna A. Vedula,et al.  Microcalcification detection using cone-beam CT mammography with a flat-panel imager. , 2004, Physics in medicine and biology.

[7]  Jeffrey H. Siewerdsen,et al.  Cone-beam CT with a flat-panel imager: noise considerations for fully 3D computed tomography , 2000, Medical Imaging.

[8]  Avinash C. Kak,et al.  Principles of computerized tomographic imaging , 2001, Classics in applied mathematics.

[9]  M D Harpen A simple theorem relating noise and patient dose in computed tomography. , 1999, Medical physics.

[10]  Jeffrey H. Siewerdsen,et al.  Three-dimensional NEQ transfer characteristics of volume CT using direct- and indirect-detection flat-panel imagers , 2003, SPIE Medical Imaging.

[11]  G. Kowalski,et al.  Reconstruction of Objects from Their Projections. The Influence of Measurement Errors on the Reconstruction , 1977, IEEE Transactions on Nuclear Science.

[12]  L. Feldkamp,et al.  Practical cone-beam algorithm , 1984 .

[13]  W. Davidon,et al.  Mathematical Methods of Physics , 1965 .

[14]  J. Boone,et al.  Dedicated breast CT: radiation dose and image quality evaluation. , 2001, Radiology.

[15]  Norbert J. Pelc,et al.  The noise power spectrum in computed X-ray tomography. , 1978 .

[16]  J. Hsieh,et al.  Nonstationary noise characteristics of the helical scan and its impact on image quality and artifacts. , 1997, Medical physics.

[17]  K Maki,et al.  Computer-assisted simulations in orthodontic diagnosis and the application of a new cone beam X-ray computed tomography. , 2003, Orthodontics & craniofacial research.

[18]  Biao Chen,et al.  Cone-beam volume CT breast imaging: feasibility study. , 2002, Medical physics.

[19]  Athanasios Papoulis,et al.  Probability, Random Variables and Stochastic Processes , 1965 .

[20]  S J Riederer,et al.  Noise Due to Photon Counting Statistics in Computed X‐Ray Tomography , 1977, Journal of computer assisted tomography.

[21]  A. Karellas,et al.  Theoretical analysis of hybrid flat-panel detector arrays for digital x-ray fluoroscopy: general sys , 2001, IEEE Sensors Journal.

[22]  J Yorkston,et al.  Empirical and theoretical investigation of the noise performance of indirect detection, active matrix flat-panel imagers (AMFPIs) for diagnostic radiology. , 1997, Medical physics.

[23]  Alvarez Re,et al.  Optimal processing of computed tomography images using experimentally measured noise properties. , 1979 .