The influence of field strength and different clinical breast MRI protocols on the outcome of texture analysis using foam phantoms

Medical Physics

Volumn 38, Issue 9, 2011, Pages 5058-5066

  Waugh, Shelley A ^a   Lerski, Richard A ^a   Bidaut, Luc ^b   Thompson, Alastair M ^b  

^a UNIVERSITY OF DUNDEE   (United Kingdom)

^b UNIVERSITY OF DUNDEE   (United Kingdom)

Author keywords

breast MRI; phantom; texture analysis; validation

Indexed keywords

BANDWIDTH; IMAGE RESOLUTION; MEDICAL IMAGING; MERGERS AND ACQUISITIONS; PHANTOMS; SCANNING; TEXTURES; WAVELET TRANSFORMS;

ACQUISITION PARAMETERS; BREAST MRI; CO-OCCURRENCE-MATRIX; GRADIENT ECHO SEQUENCES; HIGH SPATIAL RESOLUTION; HIGH TEMPORAL RESOLUTION; TEXTURE ANALYSIS; VALIDATION;

MAGNETIC RESONANCE IMAGING;

EID: 80052415568     PISSN: 00942405     EISSN: None     Source Type: Journal    
DOI: 10.1118/1.3622605     Document Type: Article

References (33)

1. R. A. Lerski, MR image texture analysis-an approach to tissue characterisation., Magn. Reson. Imaging 11, 873-887 (1993). 10.1016/0730- 725X(93)90205-R
2. G. D. Tourassi, Journey toward computer-aided diagnosis: role of image texture analysis., Radiology 213, 317-320 (1999).
3. G. Castellano, Texture analysis of medical images., Clin. Radiol. 59, 1061-1069 (2004). 10.1016/j.crad.2004.07.008
4. L. Kjaer, Texture analysis in quantitative MR imaging. Tissue characterisation of normal brain and intracranial tumours at 1.5T., Acta Radiol. 36 (2), 127-135 (1995). 10.3109/02841859509173364
5. J.-F. Nedelec, Texture analysis of the brain: from animal models to human applications., Dial. Clin. Neurosci. 6 (2), 227-233 (2004).
6. O. Yu, Existence of contralateral abnormalities revealed by texture analysis in unilateral intractable hippocampal epilepsy., Magn. Reson. Imaging 19, 1305-1310 (2001). 10.1016/S0730-725X(01)00464-7
7. D. Jirak, Texture analysis of human liver., J. Magn. Reson Imaging 15, 68-74 (2002). 10.1002/jmri.v15:1
8. T. M. Link, In vivo high resolution MRI of the calcaneus: differences in trabecular structure in osteoporosis patients., J. Bone Miner. Res. 13 (7), 1175-1182 (1998). 10.1359/jbmr.1998.13.7.1175
9. H. Langenberger, Bone homogeneity factor: an advanced tool for the assessment of osteoporotic bone structure in high resolution magnetic resonance images., Invest. Radiol. 38 (7), 467-472 (2003). 10.1097/00004424-200307000- 00013
10. P. Gibbs and L. W. Turnbull, Textural analysis of contrast-enhanced MR images of the breast., Magn. Reson. Med. 50, 92-98 (2003). 10.1002/mrm.v50:1
11. S. Sinha, Multifeature analysis of Gd-enhanced MR images of breast lesions., J. Magn. Reson Imaging 7 (6), 1016-1026 (1997). 10.1002/jmri.v7:6
12. W. Chen, Volumetric texture analysis of breast lesions on contrast enhanced magnetic resonance images., Magn. Reson. Med. 58, 562-571 (2007). 10.1002/mrm.v58:3
13. K. Holli, Characterisation of breast cancer types by texture analysis of magnetic reonance images., Acad. Radiol. 17 (2), 135-141 (2010). 10.1016/j.acra.2009.08.012
14. G. Collewet, M. Strzelecki, and F. Mariette, Influenece of MRI acquisition protocols and image intensity normalisation methods on texture classification., Magn. Reson Imaging 22, 81-91 (2004). 10.1016/j.mri.2003.09.001
15. R. A. Lerski, Multicentre magnetic resonance texture analysis trial using reticulated foam test objects., Magn. Reson Imaging 17 (7), 1025-1031 (1999). 10.1016/S0730-725X(99)00034-X
16. D. Jirak, M. Dezortova, and M. Hajek M, Phantoms for texture analysis of MR images. Long term and multi-center study., Med. Phys. 31 (3), 616-622 (2004). 10.1118/1.1646231
17. M. E. Mayerhoefer, Effects of magnetic resonance image interpolation on results of texture based pattern classification., Invest. Radiol. 44 (7), 405-411 (2009). 10.1097/RLI.0b013e3181a50a66
18. M. E. Mayerhoefer, Effects of MRI acquisition parameter variations and protocol heterogeneity on the results of texture analysis and pattern discrimination., Med. Phys. 36 (4), 1236-1243 (2009). 10.1118/1.3081408
19. M. E. Mayerhoefer, Texture analysis for tissue discrimination on T1-weighted MR images of the knee joint in a multicentre study: transferability of texture features and comparison of feature selection methods and classifiers., J. Magn. Reson Imaging 22 (5), 674-680 (2005). 10.1002/jmri.v22:5
20. L. R. Schad and A. Lundervold A, in Texture Analysis for Magnetic Resonance Imaging, edited by, M. Dezortova, M. Hajek, A. Materka, and, R. Lerski, (Med4Publishing, Prague, 2006), pp. 129-149.
21. S. Herlidou-Meme, MRI texture analysis on texture test objects, normal brain and intracranial tumours., Magn. Reson Imaging 21, 989-993 (2003). 10.1016/S0730-725X(03)00212-1
22. R. A. Lerski and L. R. Schad, The use of reticulated foam in texture test objects for magnetic resonance imaging., Magn. Reson Imaging 16 (9), 1139-1144 (1998). 10.1016/S0730-725X(98)00096-4
23. B. Daniel, R. Rakow-Penner, H. Yu, A. Sawyer-Glover, and G. H. Glover, Relaxation times of breast tissue at 1.5T and 3.0T measured using IDEAL., J. Magn. Reson Imaging 23, 87-91 (2006). 10.1002/jmri.v23:1
24. R. M. Mann, Breast MRI: guidelines from the european society of breast imaging., Eur. Radiol. 18, 1307-1318 (2008). 10.1007/s00330-008-0863-7
25. A. Radjenovic, Measurement of pharmacokinetic parameters in histologically graded invasive breast tumours using dynamic contrast enhanced MRI., Br. J. Radiol. 81, 120-128 (2008). 10.1259/bjr/98435332
26. M.-Y. Su, Pharmacokinetic parameters analysed from MR contrast enhancement kinetics of multiple malignant and benign breast lesions detected in the same patients., Technol. Cancer Res. Treat. 4, 255-264 (2005).
27. U. Hoffmann, Pharmacokinetic mapping of the breast: a new method for dynamic MR mammography., Magn. Reson. Med. 33, 506-514 (1995). 10.1002/mrm.v33:4
28. P. M. Szczpinski, Mazda 3D Editor (Technical University of Lodz, Institute of Electronics, 2007).
29. P. M. Szczpinski, MaZda - a software package for image texture analysis., Comput. Methods Programs Biomed. 94 (1), 66-76 (2009). 10.1016/j.cmpb.2008.08. 005
30. A. Materka, B11 (University of Lodz, Institute of Electronics, 2004).
31. M. Strzlecki, A. Materka, and P. Szczypinski, in Texture Analysis for Magnetic Resonance Imaging, edited by, M. Dezortova, M. Hajek, A. Materka, and, R. Lerski, (Med4Publishing, Prague, 2006), pp. 107-113.
32. R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification, 2nd ed. (Wiley, New York, 2001).
33. L. Kaufman, Measuring signal-to-noise ratios in MR imaging., Radiology 173, 265-267 (1989).