Feature analysis of hyperpolarized helium-3 pulmonary MRI: A study of asthmatics versus nonasthmatics

A computational framework is described that was developed for quantitative analysis of hyperpolarized helium‐3 MR lung ventilation image data. This computational framework was applied to a study consisting of 55 subjects (47 asthmatic and eight normal). Each subject was imaged before and after respi...

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Published inMagnetic resonance in medicine Vol. 63; no. 6; pp. 1448 - 1455
Main Authors Tustison, Nicholas J., Altes, Talissa A., Song, Gang, de Lange, Eduard E., Mugler III, John P., Gee, James C.
Format Journal Article
LanguageEnglish
Published Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.06.2010
Subjects
Online AccessGet full text
ISSN0740-3194
1522-2594
1522-2594
DOI10.1002/mrm.22390

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Abstract A computational framework is described that was developed for quantitative analysis of hyperpolarized helium‐3 MR lung ventilation image data. This computational framework was applied to a study consisting of 55 subjects (47 asthmatic and eight normal). Each subject was imaged before and after respiratory challenge and also underwent spirometry. Approximately 1600 image features were calculated from the lungs in each image. Both the image and 27 spirometric features were ranked based on their ability to characterize clinical diagnosis using a mutual information‐based feature subset selection algorithm. It was found that the top image features perform much better compared with the current clinical gold‐standard spirometric values when considered individually. Interestingly, it was also found that spirometric values are relatively orthogonal to these image feature values in terms of informational content. Magn Reson Med, 2010. © 2010 Wiley‐Liss, Inc.
AbstractList A computational framework is described that was developed for quantitative analysis of hyperpolarized helium‐3 MR lung ventilation image data. This computational framework was applied to a study consisting of 55 subjects (47 asthmatic and eight normal). Each subject was imaged before and after respiratory challenge and also underwent spirometry. Approximately 1600 image features were calculated from the lungs in each image. Both the image and 27 spirometric features were ranked based on their ability to characterize clinical diagnosis using a mutual information‐based feature subset selection algorithm. It was found that the top image features perform much better compared with the current clinical gold‐standard spirometric values when considered individually. Interestingly, it was also found that spirometric values are relatively orthogonal to these image feature values in terms of informational content. Magn Reson Med, 2010. © 2010 Wiley‐Liss, Inc.
A computational framework is described that was developed for quantitative analysis of hyperpolarized helium-3 MR lung ventilation image data. This computational framework was applied to a study consisting of 55 subjects (47 asthmatic and eight normal). Each subject was imaged before and after respiratory challenge and also underwent spirometry. Approximately 1600 image features were calculated from the lungs in each image. Both the image and 27 spirometric features were ranked based on their ability to characterize clinical diagnosis using a mutual information-based feature subset selection algorithm. It was found that the top image features perform much better compared with the current clinical gold-standard spirometric values when considered individually. Interestingly, it was also found that spirometric values are relatively orthogonal to these image feature values in terms of informational content.
A computational framework is described that was developed for quantitative analysis of hyperpolarized helium-3 MR lung ventilation image data. This computational framework was applied to a study consisting of 55 subjects (47 asthmatic and eight normal). Each subject was imaged before and after respiratory challenge and also underwent spirometry. Approximately 1600 image features were calculated from the lungs in each image. Both the image and 27 spirometric features were ranked based on their ability to characterize clinical diagnosis using a mutual information-based feature subset selection algorithm. It was found that the top image features perform much better compared with the current clinical gold-standard spirometric values when considered individually. Interestingly, it was also found that spirometric values are relatively orthogonal to these image feature values in terms of informational content. Magn Reson Med, 2010. [copy 2010 Wiley-Liss, Inc.
A computational framework is described that was developed for quantitative analysis of hyperpolarized helium-3 MR lung ventilation image data. This computational framework was applied to a study consisting of 55 subjects (47 asthmatic and eight normal). Each subject was imaged before and after respiratory challenge and also underwent spirometry. Approximately 1600 image features were calculated from the lungs in each image. Both the image and 27 spirometric features were ranked based on their ability to characterize clinical diagnosis using a mutual information-based feature subset selection algorithm. It was found that the top image features perform much better compared with the current clinical gold-standard spirometric values when considered individually. Interestingly, it was also found that spirometric values are relatively orthogonal to these image feature values in terms of informational content.A computational framework is described that was developed for quantitative analysis of hyperpolarized helium-3 MR lung ventilation image data. This computational framework was applied to a study consisting of 55 subjects (47 asthmatic and eight normal). Each subject was imaged before and after respiratory challenge and also underwent spirometry. Approximately 1600 image features were calculated from the lungs in each image. Both the image and 27 spirometric features were ranked based on their ability to characterize clinical diagnosis using a mutual information-based feature subset selection algorithm. It was found that the top image features perform much better compared with the current clinical gold-standard spirometric values when considered individually. Interestingly, it was also found that spirometric values are relatively orthogonal to these image feature values in terms of informational content.
Author Mugler III, John P.
de Lange, Eduard E.
Altes, Talissa A.
Song, Gang
Gee, James C.
Tustison, Nicholas J.
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Cites_doi 10.1259/imaging/69642424
10.1164/ajrccm.162.6.ats9-00
10.1002/jmri.1054
10.1007/11812715_10
10.1378/chest.124.6.2156
10.1109/CVPR.2000.855835
10.1016/j.acra.2006.04.017
10.1109/42.24861
10.1002/jmri.20290
10.1164/ajrccm.161.5.9903102
10.1002/jmri.20104
10.1136/thx.54.5.384
10.1109/TSMC.1979.4310076
10.1155/IJBI/2006/49515
10.1513/pats.200510-115JH
10.1148/radiology.210.3.r99fe08851
10.1109/TPAMI.2005.159
10.1109/42.668698
10.1016/0167-8655(91)80014-2
10.1148/radiol.2482071838
10.1016/j.ejrad.2004.08.002
10.1016/S1361-8415(97)85005-0
10.1164/ajrccm.164.12.2012140
10.1097/01.rli.0000262571.81771.66
10.1109/TPAMI.2003.1177156
10.1016/j.jaci.2006.12.659
10.1109/TSMC.1973.4309314
10.1002/mrm.10173
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References Woodhouse N, Wild JM, Paley MNJ, Fichele S, Said Z, Swift AJ, van Beek EJR. Combined helium-3/proton magnetic resonance imaging measurement of ventilated lung volumes in smokers compared to never-smokers. J Magn Reson Imaging 2005; 21: 365-369.
Möller HE, Chen XJ, Saam B, Hagspiel KD, Johnson GA, Altes TA, de Lange EE, Kauczor HU. MRI of the lungs using hyperpolarized noble gases. Magn Reson Med 2002; 47: 1029-1051.
Tustison NJ, Gee JC. N4ITK: Nick's N3 ITK implementation for MRI bias field correction. Insight J 2009; 2009: 1-8.
Strek ME. Difficult asthma. Proc Am Thorac Soc 2006; 3: 116-123.
Maurer CR, Rensheng Q, Raghavan V. A linear time algorithm for computing exact Euclidean distance transforms of binary images in arbitrary images. IEEE Trans Pattern Anal Mach Intell 2003; 25: 265-270.
Nakano Y, Sakai H, Muro S, Hirai T, Oku Y, Nishimura K, et al. Comparison of low attenuation areas on computed tomographic scans between inner and outer segments of the lung in patients with chronic obstructive pulmonary disease: incidence and contribution to lung function. Thorax 1999; 54: 384-389.
Nakano Y, Coxson HO, Bosan S, Rogers RM, Sciurba FC, Keenan RJ, et al. Core to rind distribution of severe emphysema predicts outcome of lung volume reduction surgery. Am J Respir Crit Care Med 2001; 164: 2195-2199.
Tustison NJ, Gee JC. Run length matrices for texture analysis. Insight J 2008; 2008: 1-6.
Haralick RM, Shanmugam K, Dinstein I. Textural features for image classification. IEEE Trans Syst Man Cybern 1973; 3: 610-621.
Peng H, Long F, Ding C. Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy. IEEE Trans Pattern Anal Mach Intell 2005; 27: 1226-1238.
Altes TA, Powers PL, Knight-Scott J, Rakes G, Platts-Mills TA, de Lange EE, Alford BA, Mugler JP, Brookeman JR. Hyperpolarized 3He MR lung ventilation imaging in asthmatics: preliminary findings. J Magn Reson Imaging 2001; 13: 378-384.
Swift AJ, Wild JM, Fichele S, Woodhouse N, Fleming S, Waterhouse J, Lawson RA, Paley MN, Van Beek EJ. Emphysematous changes and normal variation in smokers and COPD patients using diffusion 3He MRI. Eur J Radiol 2005; 54: 352-358.
Fichele S, Woodhouse N, Swift AJ, Said Z, Paley MN, Kasuboski L, Mills GH, van Beek EJ, Wild JM. MRI of helium-3 gas in healthy lungs: posture related variations of alveolar size. J Magn Reson Imaging 2004; 20: 331-335.
Bousquet J, Jeffery PK, Busse WW, Johnson M, Vignola AM. Asthma from bronchoconstriction to airways inflammation and remodeling. Am J Respir Crit Care Med 2000; 161: 1720-1745.
Lutey BA, Lefrak SS, Woods JC, Tanoli T, Quirk JD, Bashir A, Yablonskiy DA, Conradi MS, Bartel ST, Pilgram TK, Cooper JD, Gierada DS. Hyperpolarized 3He MR imaging: physiologic monitoring observations and safety considerations in 100 consecutive subjects. Radiology 2008; 248: 655-661.
Sled JG, Zijdenbos AP, Evans AC. A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans Med Imaging 1998; 17: 87-97.
Baker KM, Brand DA, Hen J. Classifying asthma. Chest 2003; 124: 2156-2163.
de Lange EE, Mugler JP, Brookeman JR, Knight-Scott J, Truwit JD, Teates CD, Daniel TM, Bogorad PL, Cates GD. Lung air spaces: MR imaging evaluation with hyperpolarized 3He gas. Radiology 1999; 210: 851-857.
Barrett WA, Mortensen EN. Interactive live-wire boundary extraction. Med Image Anal 1997; 1: 331-341.
Parraga G, Ouriadov A, Evans A, McKay S, Lam WW, Fenster A, Etemad-Rezai R, McCormack D, Giles S. Hyperpolarized 3He ventilation defects and apparent diffusion coefficients in chronic obstructive pulmonary disease: preliminary results at 3.0 tesla. Invest Radiol 2007; 42: 384-391.
Hou Z. A review on MR image intensity inhomogeneity correction. Int J Biomed Imaging 2006; 2006: 1-11.
Chen CC, DaPonte J, Fox M. Fractal feature analysis and classification in medical imaging. IEEE Trans Med Imaging 1989; 8: 133-142.
Otsu N. A thresholding selection method from gray-scale histogram. IEEE Trans Syst Man Cybern 1979; 9: 62-66.
de Lange EE, Altes TA, Patrie JT, Parmar J, Brookeman JR, Mugler JP, Platts-Mills TAE. The variability of regional airflow obstruction within the lungs of patients with asthma: assessment with hyperpolarized helium-3 magnetic resonance imaging. J Allergy Clin Immunol 2007; 119: 1072-1078.
Proceedings of the ATS workshop on refractory asthma: current understanding, recommendations, and unanswered questions. American Thoracic Society; Am J Respir crit Care Med 2000; 162: 2341-51.
Hill C, van Beek EJR. MRI of the chest: present and future. Imaging 2004; 16: 61-70.
Xu Y, van Beek EJR, Hwanjo Y, Guo J, McLennan G, Hoffman EA. Computer-aided classification of interstitial lung diseases via MDCT: 3D adaptive multiple feature method (3D AMFM). Acad Radiol 2008; 13: 969-978.
Tustison NJ, Gee JC. Stochastic fractal dimension image. Insight J 2009; 2009: 1-5.
Dasarathy BR, Holder EB. Image characterizations based on joint gray-level run-length distributions. Pattern Recog Lett 1991; 12: 497-502.
2004; 20
2001; 164
1991; 12
1989; 8
2008
2007
2006
2005; 21
2008; 13
2006; 3
2008; 248
1997; 1
2005; 27
2008; 2008
2002; 47
1998; 17
2009; 2009
2007; 119
2000
2004; 16
2000; 161
2003; 25
2000; 162
2006; 2006
2005; 54
1999; 54
1999; 210
2007; 42
2003; 124
2001; 13
1979; 9
1973; 3
e_1_2_6_30_2
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Tustison NJ (e_1_2_6_31_2) 2008; 2008
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References_xml – reference: Xu Y, van Beek EJR, Hwanjo Y, Guo J, McLennan G, Hoffman EA. Computer-aided classification of interstitial lung diseases via MDCT: 3D adaptive multiple feature method (3D AMFM). Acad Radiol 2008; 13: 969-978.
– reference: Barrett WA, Mortensen EN. Interactive live-wire boundary extraction. Med Image Anal 1997; 1: 331-341.
– reference: Nakano Y, Coxson HO, Bosan S, Rogers RM, Sciurba FC, Keenan RJ, et al. Core to rind distribution of severe emphysema predicts outcome of lung volume reduction surgery. Am J Respir Crit Care Med 2001; 164: 2195-2199.
– reference: Peng H, Long F, Ding C. Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy. IEEE Trans Pattern Anal Mach Intell 2005; 27: 1226-1238.
– reference: Tustison NJ, Gee JC. Stochastic fractal dimension image. Insight J 2009; 2009: 1-5.
– reference: Tustison NJ, Gee JC. Run length matrices for texture analysis. Insight J 2008; 2008: 1-6.
– reference: Parraga G, Ouriadov A, Evans A, McKay S, Lam WW, Fenster A, Etemad-Rezai R, McCormack D, Giles S. Hyperpolarized 3He ventilation defects and apparent diffusion coefficients in chronic obstructive pulmonary disease: preliminary results at 3.0 tesla. Invest Radiol 2007; 42: 384-391.
– reference: Dasarathy BR, Holder EB. Image characterizations based on joint gray-level run-length distributions. Pattern Recog Lett 1991; 12: 497-502.
– reference: Proceedings of the ATS workshop on refractory asthma: current understanding, recommendations, and unanswered questions. American Thoracic Society; Am J Respir crit Care Med 2000; 162: 2341-51.
– reference: Haralick RM, Shanmugam K, Dinstein I. Textural features for image classification. IEEE Trans Syst Man Cybern 1973; 3: 610-621.
– reference: Lutey BA, Lefrak SS, Woods JC, Tanoli T, Quirk JD, Bashir A, Yablonskiy DA, Conradi MS, Bartel ST, Pilgram TK, Cooper JD, Gierada DS. Hyperpolarized 3He MR imaging: physiologic monitoring observations and safety considerations in 100 consecutive subjects. Radiology 2008; 248: 655-661.
– reference: Möller HE, Chen XJ, Saam B, Hagspiel KD, Johnson GA, Altes TA, de Lange EE, Kauczor HU. MRI of the lungs using hyperpolarized noble gases. Magn Reson Med 2002; 47: 1029-1051.
– reference: Woodhouse N, Wild JM, Paley MNJ, Fichele S, Said Z, Swift AJ, van Beek EJR. Combined helium-3/proton magnetic resonance imaging measurement of ventilated lung volumes in smokers compared to never-smokers. J Magn Reson Imaging 2005; 21: 365-369.
– reference: Hou Z. A review on MR image intensity inhomogeneity correction. Int J Biomed Imaging 2006; 2006: 1-11.
– reference: Swift AJ, Wild JM, Fichele S, Woodhouse N, Fleming S, Waterhouse J, Lawson RA, Paley MN, Van Beek EJ. Emphysematous changes and normal variation in smokers and COPD patients using diffusion 3He MRI. Eur J Radiol 2005; 54: 352-358.
– reference: de Lange EE, Mugler JP, Brookeman JR, Knight-Scott J, Truwit JD, Teates CD, Daniel TM, Bogorad PL, Cates GD. Lung air spaces: MR imaging evaluation with hyperpolarized 3He gas. Radiology 1999; 210: 851-857.
– reference: Sled JG, Zijdenbos AP, Evans AC. A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans Med Imaging 1998; 17: 87-97.
– reference: Maurer CR, Rensheng Q, Raghavan V. A linear time algorithm for computing exact Euclidean distance transforms of binary images in arbitrary images. IEEE Trans Pattern Anal Mach Intell 2003; 25: 265-270.
– reference: Tustison NJ, Gee JC. N4ITK: Nick's N3 ITK implementation for MRI bias field correction. Insight J 2009; 2009: 1-8.
– reference: Baker KM, Brand DA, Hen J. Classifying asthma. Chest 2003; 124: 2156-2163.
– reference: Strek ME. Difficult asthma. Proc Am Thorac Soc 2006; 3: 116-123.
– reference: Bousquet J, Jeffery PK, Busse WW, Johnson M, Vignola AM. Asthma from bronchoconstriction to airways inflammation and remodeling. Am J Respir Crit Care Med 2000; 161: 1720-1745.
– reference: Altes TA, Powers PL, Knight-Scott J, Rakes G, Platts-Mills TA, de Lange EE, Alford BA, Mugler JP, Brookeman JR. Hyperpolarized 3He MR lung ventilation imaging in asthmatics: preliminary findings. J Magn Reson Imaging 2001; 13: 378-384.
– reference: Fichele S, Woodhouse N, Swift AJ, Said Z, Paley MN, Kasuboski L, Mills GH, van Beek EJ, Wild JM. MRI of helium-3 gas in healthy lungs: posture related variations of alveolar size. J Magn Reson Imaging 2004; 20: 331-335.
– reference: Nakano Y, Sakai H, Muro S, Hirai T, Oku Y, Nishimura K, et al. Comparison of low attenuation areas on computed tomographic scans between inner and outer segments of the lung in patients with chronic obstructive pulmonary disease: incidence and contribution to lung function. Thorax 1999; 54: 384-389.
– reference: de Lange EE, Altes TA, Patrie JT, Parmar J, Brookeman JR, Mugler JP, Platts-Mills TAE. The variability of regional airflow obstruction within the lungs of patients with asthma: assessment with hyperpolarized helium-3 magnetic resonance imaging. J Allergy Clin Immunol 2007; 119: 1072-1078.
– reference: Otsu N. A thresholding selection method from gray-scale histogram. IEEE Trans Syst Man Cybern 1979; 9: 62-66.
– reference: Chen CC, DaPonte J, Fox M. Fractal feature analysis and classification in medical imaging. IEEE Trans Med Imaging 1989; 8: 133-142.
– reference: Hill C, van Beek EJR. MRI of the chest: present and future. Imaging 2004; 16: 61-70.
– volume: 2009
  start-page: 1
  year: 2009
  end-page: 8
  article-title: N4ITK: Nick's N3 ITK implementation for MRI bias field correction
  publication-title: Insight J
– volume: 13
  start-page: 969
  year: 2008
  end-page: 978
  article-title: Computer‐aided classification of interstitial lung diseases via MDCT: 3D adaptive multiple feature method (3D AMFM)
  publication-title: Acad Radiol
– volume: 16
  start-page: 61
  year: 2004
  end-page: 70
  article-title: MRI of the chest: present and future
  publication-title: Imaging
– volume: 13
  start-page: 378
  year: 2001
  end-page: 384
  article-title: Hyperpolarized He MR lung ventilation imaging in asthmatics: preliminary findings
  publication-title: J Magn Reson Imaging
– year: 2007
– volume: 27
  start-page: 1226
  year: 2005
  end-page: 1238
  article-title: Feature selection based on mutual information: criteria of max‐dependency, max‐relevance, and min‐redundancy
  publication-title: IEEE Trans Pattern Anal Mach Intell
– volume: 210
  start-page: 851
  year: 1999
  end-page: 857
  article-title: Lung air spaces: MR imaging evaluation with hyperpolarized 3He gas
  publication-title: Radiology
– volume: 42
  start-page: 384
  year: 2007
  end-page: 391
  article-title: Hyperpolarized He ventilation defects and apparent diffusion coefficients in chronic obstructive pulmonary disease: preliminary results at 3.0 tesla
  publication-title: Invest Radiol
– volume: 20
  start-page: 331
  year: 2004
  end-page: 335
  article-title: MRI of helium‐3 gas in healthy lungs: posture related variations of alveolar size
  publication-title: J Magn Reson Imaging
– start-page: 5
  year: 2008
  end-page: 14
– start-page: 76
  year: 2006
  end-page: 83
– volume: 164
  start-page: 2195
  year: 2001
  end-page: 2199
  article-title: Core to rind distribution of severe emphysema predicts outcome of lung volume reduction surgery
  publication-title: Am J Respir Crit Care Med
– volume: 2009
  start-page: 1
  year: 2009
  end-page: 5
  article-title: Stochastic fractal dimension image
  publication-title: Insight J
– volume: 2008
  start-page: 1
  year: 2008
  end-page: 6
  article-title: Run length matrices for texture analysis
  publication-title: Insight J
– volume: 1
  start-page: 331
  year: 1997
  end-page: 341
  article-title: Interactive live‐wire boundary extraction
  publication-title: Med Image Anal
– volume: 54
  start-page: 352
  year: 2005
  end-page: 358
  article-title: Emphysematous changes and normal variation in smokers and COPD patients using diffusion He MRI
  publication-title: Eur J Radiol
– volume: 119
  start-page: 1072
  year: 2007
  end-page: 1078
  article-title: The variability of regional airflow obstruction within the lungs of patients with asthma: assessment with hyperpolarized helium‐3 magnetic resonance imaging
  publication-title: J Allergy Clin Immunol
– volume: 54
  start-page: 384
  year: 1999
  end-page: 389
  article-title: Comparison of low attenuation areas on computed tomographic scans between inner and outer segments of the lung in patients with chronic obstructive pulmonary disease: incidence and contribution to lung function
  publication-title: Thorax
– volume: 161
  start-page: 1720
  year: 2000
  end-page: 1745
  article-title: Asthma from bronchoconstriction to airways inflammation and remodeling
  publication-title: Am J Respir Crit Care Med
– volume: 2006
  start-page: 1
  year: 2006
  end-page: 11
  article-title: A review on MR image intensity inhomogeneity correction
  publication-title: Int J Biomed Imaging
– volume: 47
  start-page: 1029
  year: 2002
  end-page: 1051
  article-title: MRI of the lungs using hyperpolarized noble gases
  publication-title: Magn Reson Med
– start-page: 316
  year: 2000
  end-page: 323
– year: 2006
– volume: 25
  start-page: 265
  year: 2003
  end-page: 270
  article-title: A linear time algorithm for computing exact Euclidean distance transforms of binary images in arbitrary images
  publication-title: IEEE Trans Pattern Anal Mach Intell
– volume: 162
  start-page: 2341
  year: 2000
  end-page: 51
  article-title: Proceedings of the ATS workshop on refractory asthma: current understanding, recommendations, and unanswered questions. American Thoracic Society
  publication-title: Am J Respir crit Care Med
– volume: 3
  start-page: 116
  year: 2006
  end-page: 123
  article-title: Difficult asthma
  publication-title: Proc Am Thorac Soc
– volume: 248
  start-page: 655
  year: 2008
  end-page: 661
  article-title: Hyperpolarized He MR imaging: physiologic monitoring observations and safety considerations in 100 consecutive subjects
  publication-title: Radiology
– volume: 3
  start-page: 610
  year: 1973
  end-page: 621
  article-title: Textural features for image classification
  publication-title: IEEE Trans Syst Man Cybern
– volume: 9
  start-page: 62
  year: 1979
  end-page: 66
  article-title: A thresholding selection method from gray‐scale histogram
  publication-title: IEEE Trans Syst Man Cybern
– volume: 124
  start-page: 2156
  year: 2003
  end-page: 2163
  article-title: Classifying asthma
  publication-title: Chest
– volume: 17
  start-page: 87
  year: 1998
  end-page: 97
  article-title: A nonparametric method for automatic correction of intensity nonuniformity in MRI data
  publication-title: IEEE Trans Med Imaging
– volume: 21
  start-page: 365
  year: 2005
  end-page: 369
  article-title: Combined helium‐3/proton magnetic resonance imaging measurement of ventilated lung volumes in smokers compared to never‐smokers
  publication-title: J Magn Reson Imaging
– volume: 12
  start-page: 497
  year: 1991
  end-page: 502
  article-title: Image characterizations based on joint gray‐level run‐length distributions
  publication-title: Pattern Recog Lett
– volume: 8
  start-page: 133
  year: 1989
  end-page: 142
  article-title: Fractal feature analysis and classification in medical imaging
  publication-title: IEEE Trans Med Imaging
– ident: e_1_2_6_2_2
– ident: e_1_2_6_8_2
  doi: 10.1259/imaging/69642424
– ident: e_1_2_6_4_2
  doi: 10.1164/ajrccm.162.6.ats9-00
– ident: e_1_2_6_13_2
  doi: 10.1002/jmri.1054
– ident: e_1_2_6_23_2
  doi: 10.1007/11812715_10
– ident: e_1_2_6_7_2
  doi: 10.1378/chest.124.6.2156
– volume: 2008
  start-page: 1
  year: 2008
  ident: e_1_2_6_31_2
  article-title: Run length matrices for texture analysis
  publication-title: Insight J
– ident: e_1_2_6_35_2
  doi: 10.1109/CVPR.2000.855835
– ident: e_1_2_6_3_2
– ident: e_1_2_6_16_2
  doi: 10.1016/j.acra.2006.04.017
– ident: e_1_2_6_27_2
  doi: 10.1109/42.24861
– ident: e_1_2_6_12_2
  doi: 10.1002/jmri.20290
– ident: e_1_2_6_15_2
– volume: 2009
  start-page: 1
  year: 2009
  ident: e_1_2_6_28_2
  article-title: Stochastic fractal dimension image
  publication-title: Insight J
– ident: e_1_2_6_6_2
  doi: 10.1164/ajrccm.161.5.9903102
– ident: e_1_2_6_19_2
  doi: 10.1002/jmri.20104
– ident: e_1_2_6_24_2
  doi: 10.1136/thx.54.5.384
– ident: e_1_2_6_32_2
  doi: 10.1109/TSMC.1979.4310076
– ident: e_1_2_6_17_2
  doi: 10.1155/IJBI/2006/49515
– ident: e_1_2_6_5_2
  doi: 10.1513/pats.200510-115JH
– ident: e_1_2_6_9_2
  doi: 10.1148/radiology.210.3.r99fe08851
– ident: e_1_2_6_33_2
  doi: 10.1109/TPAMI.2005.159
– ident: e_1_2_6_20_2
  doi: 10.1109/42.668698
– ident: e_1_2_6_30_2
  doi: 10.1016/0167-8655(91)80014-2
– ident: e_1_2_6_10_2
  doi: 10.1148/radiol.2482071838
– ident: e_1_2_6_18_2
  doi: 10.1016/j.ejrad.2004.08.002
– ident: e_1_2_6_22_2
  doi: 10.1016/S1361-8415(97)85005-0
– ident: e_1_2_6_25_2
  doi: 10.1164/ajrccm.164.12.2012140
– ident: e_1_2_6_11_2
  doi: 10.1097/01.rli.0000262571.81771.66
– ident: e_1_2_6_26_2
  doi: 10.1109/TPAMI.2003.1177156
– ident: e_1_2_6_14_2
  doi: 10.1016/j.jaci.2006.12.659
– volume: 2009
  start-page: 1
  year: 2009
  ident: e_1_2_6_21_2
  article-title: N4ITK: Nick's N3 ITK implementation for MRI bias field correction
  publication-title: Insight J
– ident: e_1_2_6_29_2
  doi: 10.1109/TSMC.1973.4309314
– ident: e_1_2_6_34_2
  doi: 10.1002/mrm.10173
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Snippet A computational framework is described that was developed for quantitative analysis of hyperpolarized helium‐3 MR lung ventilation image data. This...
A computational framework is described that was developed for quantitative analysis of hyperpolarized helium-3 MR lung ventilation image data. This...
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SubjectTerms asthma
Asthma - physiopathology
Computer Simulation
feature analysis
Helium
Humans
hyperpolarized helium-3 MRI
Lung - diagnostic imaging
Magnetic Resonance Imaging - methods
mRMR algorithm
Radiography
Reference Standards
Respiratory Function Tests
Spirometry
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Title Feature analysis of hyperpolarized helium-3 pulmonary MRI: A study of asthmatics versus nonasthmatics
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