From medical images to multiple-biomarker microarrays

Medical Physics

Volumn 34, Issue 12, 2007, Pages 4944-4951

  Wagner, Robert F ^a  

^a CENTER FOR DEVICES AND RADIOLOGICAL HEALTH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOMARKERS; COMPUTERIZED TOMOGRAPHY; DIAGNOSIS; MAGNETIC RESONANCE IMAGING;

CENTRAL PROBLEMS; EMERGING TECHNOLOGIES; ILL CONDITIONED PROBLEMS; MODERN TECHNOLOGIES; MULTIPLE BIOMARKERS;

MEDICAL IMAGING;

BIOLOGICAL MARKER;

ACUTE GRANULOCYTIC LEUKEMIA; ACUTE LYMPHOBLASTIC LEUKEMIA; ALGORITHM; ARTICLE; COMPUTER ASSISTED TOMOGRAPHY; DIAGNOSTIC IMAGING; DNA MICROARRAY; GEOMETRY; HUMAN; MICROARRAY ANALYSIS; NUCLEAR MAGNETIC RESONANCE; NUCLEAR MAGNETIC RESONANCE IMAGING; NUCLEOTIDE SEQUENCE; PHYSICS; PRIORITY JOURNAL; QUANTUM MECHANICS; SIGNAL DETECTION; SIGNAL NOISE RATIO;

EID: 36649021316     PISSN: 00942405     EISSN: None     Source Type: Journal    
DOI: 10.1118/1.2805252     Document Type: Article

References (38)

1. "Prediction is difficult, especially about the future!" Y. Berra or N. Bohr? Apparently Niels Bohr is ahead in the competition for this attribution. Other household names are also high on the list, according to searches conducted by http://letterfromhere.blogspot.com/2006/12/bohr-leads- berra-but-yogi-closing-gap.html
2. H. H. Barrett and K. J. Myers, Foundations of Image Science (John Wiley and Sons, Hoboken, NJ, 2004).
3. R. Gordon, " Dose reduction in computerized tomography., " Invest. Radiol. 11, 508-517 (1976). 0020-9996
4. R. F. Wagner, D. G. Brown, and M. S. Pastel, " The application of information theory to the assessment of computed tomography., " Med. Phys. 0094-2405 10.1118/1.594559 6, 83-94 (1979).
5. K. M. Hanson, " Detectability in computed tomographic images., " Med. Phys. 0094-2405 10.1118/1.594534 6, 441-451 (1979).
6. K. M. Hanson, " Noise and contrast discrimination in computed tomography., " in Radiology of the Skull and Brain: Technical Aspects of Computed Tomography, edited by, T. H. Newton, and, D. G. Potts, (C.V. Mosby, St. Louis, 1981), Vol. 5, Chap., pp. 3941-3955.
7. R. Stanton and O. Tretiak, " Dose reduction through variable dose CT Scanning: Optimality of the filtered backprojection algorithm., " J. Comput. Assist. Tomogr. 7, 1054-1061 (1983). 0363-8715
8. K. M. Hanson, " Bayesian and related methods in reconstruction from incomplete data., in Image Recovery: Theory and Applications, edited by, H. Stark, (Academic Press, Orlando, 1987), pp. 79-125.
9. R. F. Wagner and D. G. Brown, " Unified SNR analysis of medical imaging systems., " Phys. Med. Biol. 0031-9155 10.1088/0031-9155/30/6/001 30, 489-518 (1985).
10. R. W. Redington, " Diagnostic NMR., " IEEE Trans. Med. Imaging MI-1, 230-233 (1982). 0278-0062
11. D. C. Peters, T. M. Grist, F. R. Korosec, J. E. Holden, W. F. Block, K. L. Wedding, T. J. Carroll, and C. A. Mistretta, " Undersampled projection reconstruction applied to MR angiography., " Magn. Reson. Med. 0740-3194 10.1002/(SICI)1522-2594(200001)43:1<91::AID-MRM11>3.0.CO;2-4 43, 91-101 (2000).
12. K. K. Vigen, D. C. Peters, T. M. Grist, W. F. Block, and C. A. Mistretta, " Undersampled projection-reconstruction imaging for time-resolved contrast-enhanced imaging., " Magn. Reson. Med. 0740-3194 10.1002/(SICI)1522-2594(200002)43:2<170::AID-MRM2>3.0.CO;2-P 43, 170-176 (2000).
13. C. A. Mistretta, O. Wieben, J. Velikina, W. Block, J. Perry, Y. Wu, K. Johnson, and Y. Wu, " Highly constrained backprojection for time-resolved MRI., " Magn. Reson. Med. 0740-3194 10.1002/mrm.20772 55, 30-40 (2006).
14. C. A. Mistretta, "Innovative physics boosts MRI speed, cuts CT dose," Invited article for Diagnostic Imaging magazine (August 2007), pp. 33-42, concluded on p. 54.
15. T. G. Schmidt, J. Star-Lack, N. R. Bennet, S. R. Mazin, E. G. Solomon, R. Fahrig, and N. J. Pelc, " A prototype table-top inverse-geometry volumetric CT system., " Med. Phys. 0094-2405 10.1118/1.2192887 33, 1867-1878 (2006).
16. R. F. Wagner, " Lessons from my Dinners with the Giants of Modern Image Science., " Radiat. Prot. Dosimetry 114, 4-10 (2005). 0144-8420
17. K. J. Myers, R. F. Wagner, K. M. Hanson, H. H. Barrett, and J. P. Rolland, " Human and quasi-Bayesian observers of images limited by quantum noise, object variability, and artifacts., " Proc. SPIE 2166, 180-190 (1994).
18. Details of many applications of the approach of Ref. may be found in manuscript or abstract form on the website of K. M. Hanson at Los Alamos, http://public.lanl.gov/kmh/publications
19. G. S. Burrill, Biotech 2006-20th Anniversary Report on the Industry. Life Sciences: A Changing Prescription (Burrill and Company, San Francisco, CA, 2006).
20. G. J. McLachlan, K. -A. Do, and C. Ambroise, Analyzing Microarray Gene Expression Data (Wiley, Hoboken, NJ, 2004).
21. B. D. Gallas, " Estimating the variance of the ideal linear observer's signal-detection performance from a finite number of trainers and testers., " presented at Medical Image Perception Conference X, Duke University, Durham, North Carolina (2003). Proceedings of the conference on disc available from Medical Imaging Perception Society (MIPS), or file available from brandon.gallas@fda.hhs.gov
22. V. N. Vapnik, The Nature of Statistical Learning Theory (Springer-Verlag, New York, 1995).
23. T. R. Golub, " Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring., " Science 0036-8075 10.1126/science.286.5439.531 286, 531-537 (1999).
24. T. M. Cover, " Geometrical and statistical properties of systems of linear inequalities with applications in pattern recognition., " IEEE Trans. Electron. Comput. EC-14, 326-334 (1965).
25. E. F. Petricoin, " Use of proteomic patterns in serum to identify ovarian cancer., " Lancet 359, 572-577 (2002). 0140-6736
26. D. E. Ransohoff, " Bias as a threat to the validity of cancer molecular-marker research., " Nat. Rev. Cancer 5, 142-149 (2005). 1474-175X
27. W. A. Yousef, R. F. Wagner, and M. H. Loew, " Comparison of nonparametric methods for assessing classifier performance in terms of ROC parameters., " in Applied Imagery Pattern Recognition Workshop, 2004: Proceedings of the 33rd AIPR Conference (IEEE Computer Society, Los Alamitos, CA, 2004), pp. 190-195.
28. W. A. Yousef, R. F. Wagner, and M. H. Loew, " Estimating the uncertainty in the estimated mean area under the ROC curve of a classifier., " Pattern Recognit. Lett. 26, 2600-2610 (2005). 0167-8655
29. W. A. Yousef, R. F. Wagner, and M. H. Loew, " Assessing classifiers from two independent data sets using ROC analysis: A nonparametric approach., " IEEE Trans. Pattern Anal. Mach. Intell. 28, 1809-1817 (2006) (TPAMI). 0162-8828
30. W. A. Yousef, R. F. Wagner, and M. H. Loew, " The partial area under the ROC curve: Its properties and nonparametric estimation for assessing classifier performance., " submitted to IEEE Trans. Pattern Anal. Mach. Intell., 2007.
31. S. S. Dave, " Prediction of survival in follicular lymphoma based on molecular features of tumor-infiltrating immune cells., " N. Engl. J. Med. 351, 2159-2169 (2004). 0028-4793
32. R. Tibshirani, " Immune signatures in follicular lymphoma., " N. Engl. J. Med. 352, 1496-1497 (2005).
33. H. P. Chan, B. Sahiner, R. F. Wagner, and N. Petrick, " Classifier design for computer-aided diagnosis: Effects of finite sample size on the mean performance of classical and neural network classifiers., " Med. Phys. 0094-2405 10.1118/1.598805 26, 2654-2668 (1999).
34. B. Sahiner, H. P. Chan, N. Petrick, R. F. Wagner, and L. Hadjiiski, " Feature selection and classifier performance in computer-aided diagnosis: The effect of finite sample size., " Med. Phys. 0094-2405 10.1118/1.599017 27, 1509-1522 (2000).
35. R. F. Wagner, C. E. Metz, and G. Campbell, " Assessment of medical imaging systems and computer aids: A Tutorial Review., " Acad. Radiol. 14, 723-748 (2007). 1076-6332
36. S. V. Beiden, M. A. Maloof, and R. F. Wagner, " A general model for finite-sample effects in training and testing of competing classifiers., " IEEE Trans. Pattern Anal. Mach. Intell. 25, 1561-1569 (2003). 0162-8828
37. R. M. Simon, E. L. Korn, L. M. McShane, M. D. Radmacher, G. W. Wright, and Y. Zhao, Design and Analysis of DNA Microarray Investigations (Springer-Verlag, New York, 2004).
38. D. Gur, R. F. Wagner, and H. -P. Chan, " On the repeated use of databases for testing incremental improvement of computer-aided detection schemes., " Acad. Radiol. 11, 103-105 (2004). 1076-6332