GPU-accelerated voxelwise hepatic perfusion quantification

Physics in Medicine and Biology

Volumn 57, Issue 17, 2012, Pages 5601-5616

  Wang, H ^a   Cao, Y ^a  

^a UNIVERSITY OF MICHIGAN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLINICAL APPLICATION; CLINICAL SETTINGS; COMPARTMENTAL MODEL; COMPUTATION SPEED; CONVENTIONAL METHODS; CONVOLUTION COMPUTATIONS; DYNAMIC CONTRAST ENHANCED; GPU COMPUTATION; GRAPHICS PROCESSING UNIT; LIVER PERFUSION; MR IMAGES; MULTIPLE THREADS; NONLINEAR LEAST-SQUARES FITTING; PARALLEL COMPUTATION; PERFUSION IMAGES; PERFUSION QUANTIFICATION; TIME POINTS;

COMPUTER GRAPHICS EQUIPMENT; FAST FOURIER TRANSFORMS; PROGRAM PROCESSORS; THREE DIMENSIONAL COMPUTER GRAPHICS;

PARAMETER ESTIMATION;

CONTRAST MEDIUM; DIAGNOSTIC AGENT;

ARTICLE; BIOLOGICAL MODEL; COMPUTER GRAPHICS; HUMAN; IMAGE PROCESSING; LIVER; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; SCINTIGRAPHY; VASCULARIZATION;

COMPUTER GRAPHICS; CONTRAST MEDIA; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; LIVER; MAGNETIC RESONANCE IMAGING; MODELS, BIOLOGICAL; PERFUSION IMAGING;

EID: 84865084002     PISSN: 00319155     EISSN: 13616560     Source Type: Journal    
DOI: 10.1088/0031-9155/57/17/5601     Document Type: Article

References (30)

1. Cao Y, Alspaugh J, Shen Z, Balter J M, Lawrence T S and Ten Haken R K 2006 A practical approach for quantitative estimates of voxel-by-voxel liver perfusion using DCE imaging and a compartmental model Med. Phys. 33 3057-62
2. Cao Y, Platt J F, Francis I R, Balter J M, Pan C, Normolle D, Ben-Josef E, Haken R K and Lawrence T S 2007 The prediction of radiation-induced liver dysfunction using a local dose and regional venous perfusion model Med. Phys. 34 604-12
3. Cao Y et al 2012 Prediction of liver function by using magnetic resonance-based portal venous perfusion imaging Int. J. Radiat. Oncol. Biol. Phys. (at press) http://dx.doi.org/10.1016/j.ijrobp.2012.02.037
4. Chiandussi L, Greco F, Sardi G, Vaccarino A, Ferraris C M and Curti B 1968 Estimation of hepatic arterial and portal venous blood flow by direct catheterization of the vena porta through the umbilical cord in man. Preliminary results Acta Hepatosplenol. 15 166-71
5. Daniel H 2005 Stream reduction operations for GPGPU applications GPU Gems 2 573-89
6. Dawson P 2007 Liver perfusion measurements Br. J. Radiol. 80 1024
7. Duhamel P and Vetterli M 1990 Fast Fourier transforms: a tutorial review and a state of the art Signal Process. 19 259-99
8. Feng D, Huang S C, Wang Z Z and Ho D 1996 An unbiased parametric imaging algorithm for nonuniformly sampled biomedical system parameter estimation IEEE Trans. Med. Imaging 15 512-8
9. Galassi M, Davies J, Theiler J, Gough B, Jungman G, Alken P, Booth M and Rossi F 2009 GNU Scientific Library Reference Manual 3rd edn (New York: Network Theory Ltd)
10. Goetti R, Reiner C S, Knuth A, Klotz E, Stenner F, Samaras P and Alkadhi H 2012 Quantitative perfusion analysis of malignant liver tumors: dynamic computed tomography and contrast-enhanced ultrasound Invest. Radiol. 47 18-24
11. Hagiwara M, Rusinek H, Lee V S, Losada M, Bannan M A, Krinsky G A and Taouli B 2008 Advanced liver fibrosis: diagnosis with 3D whole-liver perfusion MR imaging - initial experience Radiology 246 926-34
12. Hashimoto K et al 2006 Assessment of the severity of liver disease and fibrotic change: the usefulness of hepatic CT perfusion imaging Oncol. Rep. 16 677-83
13. Jia X, Gu X, Graves Y J, Folkerts M and Jiang S B 2011 GPU-based fast Monte Carlo simulation for radiotherapy dose calculation Phys. Med. Biol. 56 7017-31
14. Koh T S, Thng C H, Lee P S, Hartono S, Rumpel H, Goh B C and Bisdas S 2008 Hepatic metastases: in vivo assessment of perfusion parameters at dynamic contrast-enhanced MR imaging with dual-input two-compartment tracer kinetics model Radiology 249 307-20
15. Lagarias J C, Reeds J A, Wright M H and Wright P E 1998 Convergence properties of the Nelder-Mead simplex method in low dimensions SIAM J. Optim. 9 112-47
16. Leggett D A, Kelley B B, Bunce I H and Miles K A 1997 Colorectal cancer: diagnostic potential of CT measurements of hepatic perfusion and implications for contrast enhancement protocols Radiology 205 716-20
17. Materne R, Smith A M, Peeters F, Dehoux J P, Keyeux A, Horsmans Y and Van Beers B E 2002 Assessment of hepatic perfusion parameters with dynamic MRI Magn. Reson. Med. 47 135-42
18. Miyazaki S, Murase K, Yoshikawa T, Morimoto S, Ohno Y and Sugimura K 2008 A quantitative method for estimating hepatic blood flow using a dual-input single-compartment model Br. J. Radiol. 81 790-800
19. Moreland K and Angel E 2003 The FFT on a GPU Proc. ACM Conf. on Graphics Hardware pp 112-9
20. Murase K, Miyazaki S and Yang X 2007 An efficient method for calculating kinetic parameters in a dual-input single-compartment model Br. J. Radiol. 80 371-5
21. Nelder J A and Mead R 1965 A simplex method for function minimization Comput. J. 7 308-13
22. NVIDIA 2010 CUDA C programming guide (Santa Clara, CA: NVIDIA Corporation)
23. Oppenheim A V, Schafer R W and Buck J R 1999 Discrete-time Signal Processing (Upper Saddle River, NJ: Prentice-Hall)
24. Owens J D, Houston M, Luebke D, Green S, Stone J E and Phillips J C 2008 GPU Computing Proc. IEEE 96 879-99
25. Pandharipande P V, Krinsky G A, Rusinek H and Lee V S 2005 Perfusion imaging of the liver: current challenges and future goals Radiology 234 661-73
26. Pratx G and Xing L 2011 GPU computing in medical physics: a review Med. Phys. 38 2685-97
27. Press W H, Teukolsky S A, Vetterling W T and Flannery B P 2007 Numerical Recipes 3rd edition: the Art of Scientific Computing (New York: Cambridge University Press)
28. Thng C H, Koh T S, Collins D J and Koh D M 2010 Perfusion magnetic resonance imaging of the liver World J. Gastroenterol. 16 1598-609
29. Tofts P S 1997 Modeling tracer kinetics in dynamic Gd-DTPA MR imaging J. Magn. Reson. Imaging 7 91-101
30. Van Beers B E, Leconte I, Materne R, Smith A M, Jamart J and Horsmans Y 2001 Hepatic perfusion parameters in chronic liver disease: dynamic CT measurements correlated with disease severity AJR Am. J. Roentgenol. 176 667-73