Recent Advances in Chest Radiography

Published Online:Dec 1 2006https://doi.org/10.1148/radiol.2413051535

Abstract

There have been many remarkable advances in conventional thoracic imaging over the past decade. Perhaps the most remarkable is the rapid conversion from film-based to digital radiographic systems. Computed radiography is now the preferred imaging modality for bedside chest imaging. Direct radiography is rapidly replacing film-based chest units for in-department posteroanterior and lateral examinations. An exciting aspect of the conversion to digital radiography is the ability to enhance the diagnostic capabilities and influence of chest radiography. Opportunities for direct computer-aided detection of various lesions may enhance the radiologist's accuracy and improve efficiency. Newer techniques such as dual-energy and temporal subtraction radiography show promise for improved detection of subtle and often obscured or overlooked lung lesions. Digital tomosynthesis is a particularly promising technique that allows reconstruction of multisection images from a short acquisition at very low patient dose. Preliminary data suggest that, compared with conventional radiography, tomosynthesis may also improve detection of subtle lung lesions. The ultimate influence of these new technologies will, of course, depend on the outcome of rigorous scientific validation.

References

1 Ravin CE, Chotas HG. Chest radiography. Radiology 1997; 204(3): 593–600. Link, Google Scholar
2 Centers for Disease Control and Prevention. Overweight and obesity: obesity trends. Atlanta, Ga: Centers for Disease Control and Prevention, 2005. Google Scholar
3 Uppot R, Sahani D, Hahn P, Kalra M, Saini S, Mueller P. Limited by body habitus: economic and quality control issues in the ability of a radiology department to provide diagnostic imaging to a fattening population [abstract]. In: Radiological Society of North America scientific assembly and annual meeting program. Oak Brook, Ill: Radiological Society of North America, 2004; 593. Google Scholar
4 Van Metter R. Describing the signal-transfer characteristics of asymmetrical radiographic screen-film systems. Med Phys 1992;19:53–58. Crossref, Medline, Google Scholar
5 Samei E, Saunders RS Jr. The nature of the digital image. In: Goldman L, Yester MV, eds. Specifications, performance evaluation and quality assurance of radiographic and fluoroscopic systems in the digital era. Madison, Wis: Medical Physics, 2004; 103–123. Google Scholar
6 Floyd CE Jr, Baker JA, Lo JY, Ravin CE. Measurement of scatter fractions in clinical bedside radiography. Radiology 1992;183:857–861. Link, Google Scholar
7 Niklason LT, Sorenson JA, Nelson JA. Scattered radiation in chest radiography. Med Phys 1981;8:677–681. Crossref, Medline, Google Scholar
8 Samei E. Efects of anatomical structure on signal detection. In: Beutel J, Kundel HL, Van Metter RL, eds. Handbook of medical imaging. Bellingham, Wash: International Society for Optical Engineering, 2000; 655–682. Google Scholar
9 Waring JJ, Wasson WW. The imperfections of the stereoscopic manoeuvre in radiography of the chest. Radiology 1926;6:198–203. Link, Google Scholar
10 Stitik FP, Tockman MS. Radiographic screening in the early detection of lung cancer. Radiol Clin North Am 1978;16:347–366. Medline, Google Scholar
11 Kundel HL, Nodine CF, Carmody D. Visual scanning, pattern recognition and decision-making in pulmonary nodule detection. Invest Radiol 1978;13:175–181. Crossref, Medline, Google Scholar
12 Kundel HL, Revesz G, Toto L. Contrast gradient and the detection of lung nodules. Invest Radiol 1979;14:18–22. Crossref, Medline, Google Scholar
13 Samei E, Flynn MJ, Eyler WR. Detection of subtle lung nodules: relative influence of quantum and anatomic noise on chest radiographs. Radiology 1999;213:727–734. Link, Google Scholar
14 Revesz G, Kundel HL, Graber MA. The influence of structured noise on the detection of radiologic abnormalities. Invest Radiol 1974;9:479–486. Crossref, Medline, Google Scholar
15 Samei E, Flynn MJ, Peterson E, Eyler WR. Subtle lung nodules: influence of local anatomic variations on detection. Radiology 2003;228:76–84. Link, Google Scholar
16 Kundel HL. Peripheral vision, structured noise and film reader error. Radiology 1975;114:269–273. Link, Google Scholar
17 Carmody DP, Nodine CF, Kundel HL. An analysis of perceptual and cognitive factors in radiographic interpretation. Perception 1980;9:339–344. Crossref, Medline, Google Scholar
18 Nodine CF, Krupinski E, Kundel HL. A perceptually-based algorithm provides effective visual feedback to radiologists searching for lung nodules. IEEE Proc Vis Biomed Comput 1990;1:202–207. Google Scholar
19 Hessel SJ, Herman PG, Swensson RG. Improving performance by multiple interpretations of chest radiographs: effectiveness and cost. Radiology 1978;127:589–594. Link, Google Scholar
20 Haus AG, Jaskulski S. Basics of film processing in medical imaging. Madison, Wis: Medical Physics, 1997. Google Scholar
21 Van Metter R, Dickerson R. Objective performance characteristics of a new asymmetric screen-film system. Med Phys 1994;21:1483–1490. Crossref, Medline, Google Scholar
22 Dobbins J. Image quality metrics for digital systems. In: Beutel HKJ, Metter RV, eds. Handbook of medical imaging. Washington, DC: International Society for Optical Engineering, 2000; 163–222. Google Scholar
23 Samei E, Flynn MJ. An experimental comparison of detector performance for computed radiography systems. Med Phys 2002;29:447–459. Crossref, Medline, Google Scholar
24 Samei E, Flynn MJ. An experimental comparison of detector performance for direct and indirect digital radiography systems. Med Phys 2003;30:608–622. Crossref, Medline, Google Scholar
25 Samei E, Lo JY, Yoshizumi TT, et al. Comparative scatter and dose performance of slot-scan and full-field digital chest radiography systems. Radiology 2005;235:940–949. Link, Google Scholar
26 Sonoda M, Takano M, Miyahara J, Kato H. Computed radiography utilizing scanning laser stimulated luminescence. Radiology 1983;148:833–838. Link, Google Scholar
27 Fetterly KA, Schueler BA. Performance evaluation of a “dual-side read” dedicated mammography computed radiography system. Med Phys 2003;30:1843–1854. Crossref, Medline, Google Scholar
28 Schaetzing R. Computed radiography technology. In: Samei E, Flynn MJ, eds. 2003 Syllabus: categorical course in diagnostic radiology physics—advances in digital radiography. Oak Brook, Ill: Radiological Society of North America, 2003; 7–22. Google Scholar
29 Leblans P, Struye L, Willems P. A new needle-crystalline computed radiography detector. J Digit Imaging 2000;13:117–120. Crossref, Medline, Google Scholar
30 Siewerdsen JH, Antonuk LE, el-Mohri Y, et al. Empirical and theoretical investigation of the noise performance of indirect detection, active matrix flat-panel imagers (AMFPIs) for diagnostic radiology. Med Phys 1997;24:71–89. Crossref, Medline, Google Scholar
31 Lee DL, Cheung LK, Rodricks B, Powell GF. Improved imaging performance of a 14 × 17-inch direct radiography system using Se/TFT detector. In: Medical imaging 1998: physics of medical imaging, Feb 22–24 1998. San Diego, Calif: International Society for Optical Engineering, 1998; 14–23. Google Scholar
32 Zhao W, Blevis I, Germann S, Rowlands JA, Waechter D, Huang Z. Digital radiology using active matrix readout of amorphous selenium: construction and evaluation of a prototype real-time detector. Med Phys 1997;24:1834–1843. Crossref, Medline, Google Scholar
33 Yorkston J. Digital radiographic technology. In: Samei E, Flynn MJ, eds. 2003 Syllabus: categorical course in diagnostic radiology physics—advances in digital radiography. Oak Brook, Ill: Radiological Society of North America, 2003; 23–36. Google Scholar
34 Samei E. Performance of digital radiography detectors: factors affecting sharpness and noise. In: Samei E, Flynn MJ, eds. 2003 Syllabus: categorical course in diagnostic radiology physics—advances in digital radiography. Oak Brook, Ill: Radiological Society of North America, 2003; 49–61. Google Scholar
35 Yaffe MJ, Rowlands JA. X-ray detectors for digital radiography. Phys Med Biol 1997;42:1–39. Crossref, Medline, Google Scholar
36 Sorenson JA, Niklason LT, Knutti DF. Performance characteristics of improved antiscatter grids. Med Phys 1980;7:525–528. Crossref, Medline, Google Scholar
37 Barnes GT, Moreland RF, Yester MV, Witten DM. The scanning grid: a novel and effective bucky movement. Radiology 1980;135:765–767. Link, Google Scholar
38 Sorenson JA, Floch J. Scatter rejection by air gaps: an empirical model. Med Phys 1985;12:308–316. Crossref, Medline, Google Scholar
39 Sorenson JA, Nelson JA, Niklason LT, Jacobsen SC. Rotating disk device for slit radiography of the chest. Radiology 1980;134:227–231. Link, Google Scholar
40 Plenkovich D, Sorenson JA, Kruger RA. Scatter rejection by electronic collimation. Med Phys 1986;13:158–163. Crossref, Medline, Google Scholar
41 Barnes GT, Brezovich IA, Witten DM. Scanning multiple slit assembly: a practical and efficient device to reduce scatter. AJR Am J Roentgenol 1977;129:497–501. Crossref, Medline, Google Scholar
42 Chotas HG, Floyd CE Jr, Dobbins JT 3rd, Lo JY, Ravin CE. Scatter fractions in AMBER imaging. Radiology 1990;177:879–880. Link, Google Scholar
43 Samei E, Saunders RS, Lo JY, et al. Fundamental imaging characteristics of a slot-scan digital chest radiographic system. Med Phys 2004;31:2687–2698. Crossref, Medline, Google Scholar
44 Holdsworth DW, Gerson RK, Fenster A. A time-delay integration charge-coupled device camera for slot-scanned digital radiography. Med Phys 1990;17:876–886. Crossref, Medline, Google Scholar
45 Mainprize JG, Ford NL, Yin S, Tumer T, Yaffe MJ. A slot-scanned photodiode-array/CCD hybrid detector for digital mammography. Med Phys 2002;29:214–225. Crossref, Medline, Google Scholar
46 Haus AG. Advances in film processing systems technology and quality control in medical imaging. Madison, Wis: Medical Physics, 2001. Google Scholar
47 Seibert JA. Digital radiographic image presentation: preprocessing methods. In: Samei E, Flynn MJ, eds. 2003 Syllabus: categorical course in diagnostic radiology physics—advances in digital radiography. Oak Brook, Ill: Radiological Society of North America, 2003; 53–70. Google Scholar
48 Prokop M, Neitzel U, Schaefer-Prokop C. Principles of image processing in digital chest radiography. J Thorac Imaging 2003;18:148–164. Crossref, Medline, Google Scholar
49 Flynn MJ. Processing digital radiographs of specific body parts. In: Samei E, Flynn MJ, eds. 2003 Syllabus: categorical course in diagnostic radiology physics—advances in digital radiography. Oak Brook, Ill: Radiological Society of North America, 2003; 71–78. Google Scholar
50 Vuylsteke P, Schoeters EP. Multiscale image contrast amplification (MUSICA). In: Loew, MH, ed. Proceedings of SPIE: medical imaging 1994—image processing. Vol 2167. Bellingham, Wash: International Society for Optical Engineering, 2001; 551–560. Google Scholar
51 Uffmann M, Prokop M, Kupper W, Mang T, Fiedler V, Schaefer-Prokop C. Soft-copy reading of digital chest radiographs: effect of ambient light and automatic optimization of monitor luminance. Invest Radiol 2005;40:180–185. Crossref, Medline, Google Scholar
52 Oschatz E, Prokop M, Scharitzer M, Weber M, Balassy C, Schaefer-Prokop C. Comparison of liquid crystal versus cathode ray tube display for the detection of simulated chest lesions. Eur Radiol 2005;15:1472–1476. Crossref, Medline, Google Scholar
53 Scharitzer M, Prokop M, Weber M, Fuchsjager M, Oschatz E, Schaefer-Prokop C. Detectability of catheters on bedside chest radiographs: comparison between liquid crystal display and high-resolution cathode-ray tube monitors. Radiology 2005;234(2):611–616. Link, Google Scholar
54 Balassy C, Prokop M, Weber M, Sailer J, Herold CJ, Schaefer-Prokop C. Flat-panel display (LCD) versus high-resolution gray-scale display (CRT) for chest radiography: an observer preference study. AJR Am J Roentgenol 2005;184:752–756. Crossref, Medline, Google Scholar
55 Samei E, Badano A, Chakraborty D, et al. Assessment of display performance for medical imaging systems. Madison, Wis: Medical Physics, 2005. Google Scholar
56 Badano A, Gagne RM, Jennings RJ, Drilling SE, Imhoff BR, Muka E. Noise in flat-panel displays with subpixel structure. Med Phys 2004;31:715–723. Crossref, Medline, Google Scholar
57 Badano A, Flynn MJ, Martin S, Kanicki J. Angular dependence of the luminance and contrast in medical monochrome liquid crystal displays. Med Phys 2003;30:2602–2613. Crossref, Medline, Google Scholar
58 Samei E, Wright SL. Effect of viewing angle response on DICOM compliance of liquid crystal displays. In: Ratib OM, Huang HK, eds. Proceedings of SPIE: medical imaging 2004—PACS and imaging informatics. Vol 5371. Bellingham, Wash: International Society for Optical Engineering, 2004; 170–177. Google Scholar
59 Averbukh AN, Channin DS, Flynn MJ. Assessment of a novel, high-resolution, color, AMLCD for diagnostic medical image display: luminance performance and DICOM calibration. J Digit Imaging 2003;16:270–279. Crossref, Medline, Google Scholar
60 Samei E, Badano A, Chakraborty D, et al. Assessment of display performance for medical imaging systems: executive summary of AAPM TG18 report. Med Phys 2005;32:1205–1225. Crossref, Medline, Google Scholar
61 Plewes DB, Wandtke JC. Improved lung nodule detection with an equalized image. In: Gray JE, Hendee WR, eds. Proceedings of SPIE: application of optical instrumentation in medicine VIII. Vol 233. Bellingham, Wash: International Society for Optical Engineering, 1980; 183–189. Google Scholar
62 Kool LJ, Busscher DL, Vlasbloem H, et al. Advanced multiple-beam equalization radiography in chest radiology: a simulated nodule detection study. Radiology 1988;169:35–39. Link, Google Scholar
63 Wandtke JC, Plewes DB, McFaul JA. Improved pulmonary nodule detection with scanning equalization radiography. Radiology 1988;169:23–27. Link, Google Scholar
64 Kamimura R, Takashima T. Clinical application of single dual-energy subtraction technique with digital storage-phosphor radiography. J Digit Imaging 1995;8:21–24. Crossref, Google Scholar
65 Kelcz F, Zink FE, Peppler WW, Kruger DG, Ergun DL, Mistretta CA. Conventional chest radiography vs dual-energy computed radiography in the detection and characterization of pulmonary nodules. AJR Am J Roentgenol 1994;162:271–278. Crossref, Medline, Google Scholar
66 Kido S, Ikezoe J, Naito H, et al. Clinical evaluation of pulmonary nodules with single-exposure dual-energy subtraction chest radiography with an iterative noise-reduction algorithm. Radiology 1995;194:407–412. Link, Google Scholar
67 Oestmann JW, Greene R, Rhea JT, et al. “Single exposure” dual-energy digital radiography in the detection of pulmonary nodules and calcifications. Invest Radiol 1989;24(7):517–521. Crossref, Medline, Google Scholar
68 Hartman TE. Dual-energy radiography. Semin Roentgenol 1997;32:45–49. Crossref, Medline, Google Scholar
69 Jacobson B. Dichromatic absorption radiography: dichromatography. Acta Radiol 1953;39:437–452. Crossref, Medline, Google Scholar
70 Ishigaki T, Sakuma S, Ikeda M. One-shot dual-energy subtraction chest imaging with computed radiography: clinical evaluation of film images. Radiology 1988;168:67–72. Link, Google Scholar
71 Ergun DL, Mistretta CA, Brown DE, et al. Single-exposure dual-energy computed radiography: improved detection and processing. Radiology 1990;174:243–249. Link, Google Scholar
72 Stewart BK, Huang HK. Single-exposure dual-energy computed radiography. Med Phys 1990;17:866–875. Crossref, Medline, Google Scholar
73 Sabol JM, Avinash GB, Nicolas F, Claus BE, Zhao J, Dobbins JT III. Development and characterization of a dual-energy subtraction imaging system for chest radiography based on CsI:Tl amorphous silicon flat-panel technology. In: Antonuk LE, Yaffe MJ, eds. Proceedings of SPIE: medical imaging 2001—physics of medical imaging. Vol 4320. Bellingham, Wash: International Society for Optical Engineering, 2001; 399–408. Google Scholar
74 Shaw CG, Plewes DB. Effects of scattered radiation and veiling glare in dual-energy tissue-bone imaging: a theoretical analysis. Med Phys 1987;14:956–967. Crossref, Medline, Google Scholar
75 Kruger DG, Zink F, Peppler WW, Ergun DL, Mistretta CA. A regional convolution kernel algorithm for scatter correction in dual-energy images: comparison to single-kernel algorithms. Med Phys 1994;21:175–184. Crossref, Medline, Google Scholar
76 Hinshaw DA, Dobbins JT III. Recent progress in noise reduction and scatter correction in dual-energy imaging. In: Van Metter RL, Beutel J, eds. Proceedings of SPIE: medical imaging 1995—physics of medical imaging. Vol 2432. Bellingham, Wash: International Society for Optical Engineering, 1995; 134–142. Google Scholar
77 Alvarez RE, Macovski A. Energy-selective reconstructions in x-ray computerized tomography. Phys Med Biol 1976;21:733–744. Crossref, Medline, Google Scholar
78 Cardinal HN, Fenster A. An accurate method for direct dual-energy calibration and decomposition. Med Phys 1990;17:327–341. Crossref, Medline, Google Scholar
79 Warp RJ, Dobbins JT 3rd. Quantitative evaluation of noise reduction strategies in dual-energy imaging. Med Phys 2003;30:190–198. Crossref, Medline, Google Scholar
80 Dobbins JT III, Warp RJ. Dual-energy methods for tissue discrimination in chest radiography. In: Samei E, Flynn MJ, eds. 2003 Syllabus: categorical course in diagnostic radiology physics—advances in digital radiography. Oak Brook, Ill: Radiological Society of North America, 2003; 173–180. Google Scholar
81 Fraser RG, Hickey NM, Niklason LT, et al. Calcification in pulmonary nodules: detection with dual-energy digital radiography. Radiology 1986;160:595–601. Link, Google Scholar
82 Fischbach F, Freund T, Rottgen R, Engert U, Felix R, Ricke J. Dual-energy chest radiography with a flat-panel digital detector: revealing calcified chest abnormalities. AJR Am J Roentgenol 2003;181:1519–1524. Crossref, Medline, Google Scholar
83 Ricke J, Fischbach F, Freund T, et al. Clinical results of CsI-detector-based dual-exposure dual energy in chest radiography. Eur Radiol 2003;13:2577–2582. Crossref, Medline, Google Scholar
84 Gilkeson RC, Novak RD, Sachs P. Digital radiography with dual-energy subtraction: improved evaluation of cardiac calcification. AJR Am J Roentgenol 2004;183:1233–1238. Crossref, Medline, Google Scholar
85 Barnes GT, Sabbagh EA, Chakraborty DP, et al. A comparison of dual-energy digital radiography and screen-film imaging in the detection of subtle interstitial pulmonary disease. Invest Radiol 1989;24:585–591. Crossref, Medline, Google Scholar
86 Kano A, Doi K, MacMahon H, Hassell D, Giger M. Digital image subtraction of temporally sequential chest images for detection of interval change. Med Phys 1994;21:453–461. Crossref, Medline, Google Scholar
87 Ishida T, Ashizawa K, Engelmann R, Katsuragawa S, MacMahon H, Doi K. Application of temporal subtraction for detection of interval changes on chest radiographs: improvement of subtraction images using automated initial image matching. J Digit Imaging 1999;12:77–86. Crossref, Medline, Google Scholar
88 Ishida T, Katsuragawa S, Nakamura K, MacMahon H, Doi K. Iterative image warping technique for temporal subtraction of sequential chest radiographs to detect interval change. Med Phys 1999;26:1320–1329. Crossref, Medline, Google Scholar
89 Zhao H, Lo SCB, Freedman MT, Mun SK. Automatic temporal subtraction of chest radiographs and its enhancement for lung cancers. In: Sonka M, Hanson KM, eds. Proceedings of SPIE: medical imaging 2001—image processing. Vol 4322. Bellingham, Wash: International Society for Optical Engineering, 2001; 1867–1872. Google Scholar
90 MacMahon H. Dual-energy and temporal subtraction digital chest radiography. In: 2003 Syllabus: categorical course in diagnostic radiology physics—advances in digital radiography. Oak Brook, Ill: Radiological Society of North America, 2003; 181–188. Google Scholar
91 Difazio MC, Macmahon H, Xu XW, et al. Digital chest radiography: effect of temporal subtraction images on detection accuracy. Radiology 1997;202:447–452. Link, Google Scholar
92 MacMahon H, Engelmann RM, Roe C, Behlen FM, Hoffmann KR, Doi K. Use of temporal subtraction for detection of early lung cancer: results of observer test [abstract]. Radiology 1998;209(P):543. Link, Google Scholar
93 Nakagawa K, Oosawa A, Tanaka H, Ohtomo K. Clinical effectiveness of improved temporal subtraction for digital chest radiographs. In: Chakraborty D, Krupinski EA, eds. Proceedings of SPIE: medical imaging 2002—image perception, observer performance, and technology assessment. Vol 4686. Bellingham, Wash: International Society for Optical Engineering, 2002; 319–325. Google Scholar
94 Kakeda S, Nakamura K, Kamada K, et al. Improved detection of lung nodules by using a temporal subtraction technique. Radiology 2002;224:145–151. Link, Google Scholar
95 Uozumi T, Nakamura K, Watanabe H, et al. ROC analysis of detection of metastatic pulmonary nodules on digital chest radiographs with temporal subtraction. Acad Radiol 2001;8:871–878. Crossref, Medline, Google Scholar
96 Abe H, MacMahon H, Engelmann R, et al. Computer-aided diagnosis in chest radiography: results of large-scale observer tests at the 1996–2001 RSNA scientific assemblies. RadioGraphics 2003;23:255–265. Link, Google Scholar
97 Tsubamoto M, Johkoh T, Kozuka T, et al. Temporal subtraction for the detection of hazy pulmonary opacities on chest radiography. AJR Am J Roentgenol 2002;179:467–471. Crossref, Medline, Google Scholar
98 Okazaki H, Nakamura K, Watanabe H, et al. Improved detection of lung cancer arising in diffuse lung diseases on chest radiographs using temporal subtraction. Acad Radiol 2004;11:498–505. Crossref, Medline, Google Scholar
99 Johkoh T, Kozuka T, Tomiyama N, et al. Temporal subtraction for detection of solitary pulmonary nodules on chest radiographs: evaluation of a commercially available computer-aided diagnosis system. Radiology 2002;223:806–811. Link, Google Scholar
100 Ziedses des Plantes BG. Eine neue methode zur differenzierung in der roentgenographie (planigraphie). Acta Radiol 1932;000:182–192. Google Scholar
101 Warp RJ, Godfrey DJ, Dobbins JT III. Applications of matrix inverse tomosynthesis. In: Dobbins JT III, Boone JM, eds. Proceedings of SPIE: medical imaging 2000—physics of medical imaging. Vol 3977. Bellingham, Wash: International Society for Optical Engineering, 2000; 376–383. Google Scholar
102 Godfrey DJ, Warp RJ, Dobbins JT III. Optimization of matrix inverse tomosynthesis. In: Antonuk LE, Yaffe MJ, eds. Proceedings of SPIE: medical imaging 2001—physics of medical imaging. Vol 4320. Bellingham, Wash: International Society for Optical Engineering, 2001; 696–704. Google Scholar
103 Godfrey DJ, Rader A, Dobbins JT III. Practical strategies for the clinical implementation of matrix inversion tomosynthesis (MITS). In: Yaffe MJ, Antonuk LE, eds. Proceedings of SPIE: medical imaging 2003—physics of medical imaging. Vol 5030. Bellingham, Wash: International Society for Optical Engineering, 2003; 379–390. Google Scholar
104 Dobbins JT 3rd, Godfrey DJ. Digital x-ray tomosynthesis: current state of the art and clinical potential. Phys Med Biol 2003;48:R65–R106. Crossref, Medline, Google Scholar
105 Dobbins JT III, Godfrey DJ, McAdams HP. Chest tomosynthesis. In: Samei E, Flynn MJ, eds. 2003 Syllabus: categorical course in diagnostic radiology physics—advances in digital radiography. Oak Brook, Ill: Radiological Society of North America, 2003; 211–226. Google Scholar
106 Lauritsch G, Harer WH. Theoretical framework for filtered back projection in tomosynthesis. In: Hanson KM, ed. Proceedings of SPIE: medical imaging 1998—image processing. Vol 3338. Bellingham, Wash: International Society for Optical Engineering, 1998; 1127–1137. Google Scholar
107 Stevens GM, Fahrig R, Pelc NJ. Filtered backprojection for modifying the impulse response of circular tomosynthesis. Med Phys 2001;28:372–380. Crossref, Medline, Google Scholar
108 Ruttimann UE, Groenhuis RA, Webber RL. Restoration of digital multiplane tomosynthesis by a constrained iteration method. IEEE Trans Med Imaging 1984;3:141–148. Crossref, Medline, Google Scholar
109 Godfrey DJ, McAdams HP, Dobbins JT 3rd. Optimization of the matrix inversion tomosynthesis (MITS) impulse response and modulation transfer function characteristics for chest imaging. Med Phys 2006;33:655–667. Crossref, Medline, Google Scholar
110 McAdams HP, Godfrey DJ, Dobbins JT III. Digital tomosynthesis for improved lung nodule detection: initial clinical experience [abstract]. In: Radiological Society of North America scientific assembly and annual meeting program. Oak Brook, Ill: Radiological Society of North America, 2003; 524. Google Scholar
111 Doi K. Overview on research and development of computer-aided diagnostic schemes. Semin Ultrasound CT MR 2004;25:404–410. Crossref, Medline, Google Scholar
112 van Ginneken B, ter Haar Romeny BM, Viergever MA. Computer-aided diagnosis in chest radiography: a survey. IEEE Trans Med Imaging 2001;20:1228–1241. Crossref, Medline, Google Scholar
113 MacMahon H, Engelmann R, Behlen FM, et al. Computer-aided diagnosis of pulmonary nodules: results of a large-scale observer test. Radiology 1999;213:723–726. Link, Google Scholar
114 Kobayashi T, Xu XW, MacMahon H, Metz CE, Doi K. Effect of a computer-aided diagnosis scheme on radiologists' performance in detection of lung nodules on radiographs. Radiology 1996;199:843–848. Link, Google Scholar
115 Shiraishi J, Abe H, Engelmann R, Doi K. Effect of high sensitivity in a computerized scheme for detecting extremely subtle solitary pulmonary nodules in chest radiographs: observer performance study. Acad Radiol 2003;10:1302–1311. Crossref, Medline, Google Scholar
116 Marten K, Seyfarth T, Auer F, et al. Computer-assisted detection of pulmonary nodules: performance evaluation of an expert knowledge-based detection system in consensus reading with experienced and inexperienced chest radiologists. Eur Radiol 2004;14(10):1930–1938. Crossref, Medline, Google Scholar
117 Freedman MT, Osicka T, Lo SCB, et al. Computer-aided detection of lung cancer on chest radiographs: effect of machine CAD true positive/false negative detections on radiologists' confidence level. In: Chakraborty D, Eckstein MP, eds. Proceedings of SPIE: medical imaging 2004—image perception, observer performance, and technology assessment. Vol 5372. Bellingham, Wash: International Society for Optical Engineering, 2004; 185–191. Google Scholar
118 Osicka T, Freedman MT, Lo SCB, et al. Computer-aided detection of lung cancer on chest radiographs: differences in the interpretation time of radiologist's showing vs. not showing improvement with CAD. In: Chakraborty D, Krupinski EA, eds. Proceedings of SPIE: medical imaging 2003—image perception, observer performance, and technology assessment. Vol 5034. Bellingham, Wash: International Society for Optical Engineering, 2003; 483–494. Google Scholar
119 Freedman M. Improved small volume lung cancer detection with computer-aided detection: database characteristics and imaging of response to breast cancer risk reduction strategies. Ann N Y Acad Sci 2004;1020:175–189. Crossref, Medline, Google Scholar
120 Kakeda S, Moriya J, Sato H, et al. Improved detection of lung nodules on chest radiographs using a commercial computer-aided diagnosis system. AJR Am J Roentgenol 2004;182:505–510. Crossref, Medline, Google Scholar
121 Shiraishi J, Abe H, Engelmann R, Aoyama M, MacMahon H, Doi K. Computer-aided diagnosis to distinguish benign from malignant solitary pulmonary nodules on radiographs: ROC analysis of radiologists' performance—initial experience. Radiology 2003;227:469–474. Link, Google Scholar
122 Monnier-Cholley L, MacMahon H, Katsuragawa S, Morishita J, Ishida T, Doi K. Computer-aided diagnosis for detection of interstitial opacities on chest radiographs. AJR Am J Roentgenol 1998;171:1651–1656. Crossref, Medline, Google Scholar
123 Ashizawa K, MacMahon H, Ishida T, et al. Effect of an artificial neural network on radiologists' performance in the differential diagnosis of interstitial lung disease using chest radiographs. AJR Am J Roentgenol 1999;172:1311–1315. Crossref, Medline, Google Scholar
124 Abe H, Ashizawa K, Li F, et al. Artificial neural networks (ANNs) for differential diagnosis of interstitial lung disease: results of a simulation test with actual clinical cases. Acad Radiol 2004;11:29–37. Crossref, Medline, Google Scholar
125 Nakamori N, Doi K, MacMahon H, Sasaki Y, Montner S. Effect of heart-size parameters computed from digital chest radiographs on detection of cardiomegaly: potential usefulness for computer-aided diagnosis. Invest Radiol 1991;26:546–550. Crossref, Medline, Google Scholar
126 Abe K, Doi K, MacMahon H, et al. Computer-aided diagnosis in chest radiography: preliminary experience. Invest Radiol 1993;28:987–993. Crossref, Medline, Google Scholar
127 Sanada S, Doi K, MacMahon H. Image feature analysis and computer-aided diagnosis in digital radiography: automated detection of pneumothorax in chest images. Med Phys 1992;19:1153–1160. Crossref, Medline, Google Scholar
128 Ko JP, Betke M. Chest CT: automated nodule detection and assessment of change over time—preliminary experience. Radiology 2001;218:267–273. Link, Google Scholar
129 van Ginneken B, Katsuragawa S, Romeny BM, Doi K. Automatic detection of abnormalities in chest radiographs using local texture analysis. IEEE Trans Med Imaging 2002;21:139–149. Crossref, Medline, Google Scholar
130 Summers RM. Road maps for advancement of radiologic computer-aided detection in the 21st century [editorial]. Radiology 2003;229:11–13. Link, Google Scholar

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