A Monte Carlo-based model for simulation of digital chest tomosynthesis

Radiation Protection Dosimetry

Volumn 139, Issue 1-3, 2010, Pages 159-163

  Ullman, Gustaf ^a   Dance, David R ^b   Sandborg, Michael ^a   Carlsson, Gudrun Alm ^a   Svalkvist, Angelica ^c,d   Båth, Magnus ^c,d  

^a LINKÖPING UNIVERSITY   (Sweden)

^b ROYAL SURREY COUNTY HOSPITAL   (United Kingdom)

^c UNIVERSITY OF GOTHENBURG   (Sweden)

^d SAHLGRENSKA UNIVERSITY HOSPITAL   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; BIOLOGICAL MODEL; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; HUMAN; IMAGE QUALITY; METHODOLOGY; MONTE CARLO METHOD; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; THORAX RADIOGRAPHY;

ALGORITHMS; COMPUTER SIMULATION; HUMANS; MODELS, BIOLOGICAL; MODELS, STATISTICAL; MONTE CARLO METHOD; PHANTOMS, IMAGING; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; RADIOGRAPHY, THORACIC; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 77953330954     PISSN: 01448420     EISSN: None     Source Type: Journal    
DOI: 10.1093/rpd/ncq079     Document Type: Article

References (12)

1. Samei, E., Flynn, M. J. and Eyler, W. R. Detection of subtle lung nodules: relative influence of quantum and anatomic noise on chest radiographs. Radiology 213 (3), 727-734 (1999).
2. Håkansson, M., Båth, M., Börjesson, S., Kheddache, S., Grahn, A., Ruschin, M., Tingberg, A., Mattsson, S. and Månsson, L. G. Nodule detection in digital chest radiography: summary of the RADIUS chest trial. Radiat. Prot. Dosimetry 114, 114-120 (2005).
3. Vikgren, J., Zachrisson, S., Svalkvist, A., Johnsson, Å. A., Boijsen, M., Flinck, A., Kheddache, S. and Båth, M. Comparison of chest tomosynthesis and chest radiography for detection of pulmonary nodules: human observer study of clinical cases. Radiology 249 (3), 1034-1041 (2008).
4. Dobbins, J. T. and Godfrey, D. J. Digital x-ray tomosynthesis: current state of the art and clinical potential. Phys. Med. Biol. 48, R65-R106 (2003).
5. Pineda, A. R., Yoon, S., Paik, D. S. and Fahrig, R. Optimization of a tomosynthesis system for the detection of lung nodules. Med. Phys. 33 (5), 1372-1379 (2006).
6. Godfrey, D. J., McAdams, H. P. and Dobbins, J. T. Optimization of the matrix inversion tomosynthesis (MITS) impulse response and modulation transfer function characteristics for chest imaging. Med. Phys. 33 (3), 655-667 (2006).
7. Malusek, A. Calculation of scatter in cone beam CT: steps towards a virtual tomograph. Linköping University Medical Dissertations No. 1051, 2008. ISBN 978-91-7393-951-5, ISSN 0345-0082.
8. Ullman, G. Quantifying image quality in diagnostic radiology using simulation of the imaging system and model observers. Linköping University Medical Dissertations No. 1050, 2008. ISBN 978-91-7393-952-2, ISSN 0345-0082.
9. Sandborg, M., Dance, D. R., Persliden, J. and Carlsson, G. A. A Monte Carlo program for the calculation of contrast, noise and absorbed dose in diagnostic radiology. Comput. Methods Programs Biomed. 42 (3), 167-180 (1994).
10. Salvat, F., Fernándes-Varea, J. M. and Sempau, J. PENELOPE-A code system for Monte Carlo simulation of electron and photon transport (Issy-les-Moulineaux, France: Nuclear Energy Agency OECD NEA) (2003).
11. Persliden, J. and Carlsson, G. A. Calculation of the small-angle distribution of scattered photons in diagnostic radiology using a Monte Carlo collision density estimator. Med. Phys. 13, 19-24 (1986).
12. Båth, M., Håkansson, M., Tingberg, A. and Månsson, L. G. Method of simulating dose reduction for digital radiographic systems. Radiat. Prot. Dosimetry 114, 253-259 (2005).