Aspects of computer-aided detection (CAD) and volumetry of pulmonary nodules using multislice CT

British Journal of Radiology

Volumn 78, Issue SPEC. ISS., 2005, Pages

  Wiemker, R ^a   Rogalla, P ^b   Blaffert, T ^a   Sifri, D ^c   Hay, O ^c   Shah, E ^c   Truyen, R ^c   Fleiter, T ^d  

^a PHILIPS RESEARCH LABORATORIES   (Germany)

^b HUMBOLDT UNIVERSITY   (Germany)

^c PHILIPS HEALTHCARE   (United States)

^d UNIVERSITY HOSPITALS OF CLEVELAND   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED TOMOGRAPHY; COMPUTER PROGRAM; DIAGNOSTIC ACCURACY; DIAGNOSTIC IMAGING; DIFFERENTIAL DIAGNOSIS; HIGH RESOLUTION COMPUTER TOMOGRAPHY; HUMAN; LUNG NODULE; MULTISLICE COMPUTER TOMOGRAPHY; QUALITY CONTROL; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING; TUMOR GROWTH; TUMOR VOLUME;

DIAGNOSIS, DIFFERENTIAL; FALSE POSITIVE REACTIONS; HUMANS; LUNG DISEASES; LUNG NEOPLASMS; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; TOMOGRAPHY, X-RAY COMPUTED;

EID: 21644461077     PISSN: 00071285     EISSN: None     Source Type: Journal    
DOI: 10.1259/bjr/30281702     Document Type: Article

References (45)

1. Prokop M, Galanski M. Spiral and multislice computed tomography of the body. Stuttgart, Germany: Thieme Medical Publishers, 2003.
2. Webb WR, Müller NL, Naidich DP. High resolution CT of the lung (2nd edn). Philadelphia, PA: Lippincott-Raven Publishers, 1996.
3. Ries LAG, Eisner MP, Kosary CL, Hankey BF, Miller BA, Clegg L, et al. In: Feuer EJ, Edwards BK, editors. SEER Cancer statistics review. 1975-2000. Bethesda, MD: National Cancer Institute. http://www.cancer.gov/statistics [accessed 14 November 2004].
4. Bach PB, Kelley MJ, Tate RC, McCrory DC. Screening for lung cancer: a review of the current literature. Chest 2003;123:72S-82S.
5. Henschke CI, McCauley DI, Yankelevitz DF, Naidich DP, McGuinness G, Miettinen OS, et al. Early lung cancer action project: overall design and findings from baseline screening. Lancet 1999;354:99-105.
6. Diederich S, Wormanns D, Semik M, Thomas M, Lenzen H, Roos N, et al. Screening for early lung cancer with low-dose spiral CT: prevalence in 817 asymptomatic smokers. Radiology 2002;222:773-81.
7. Wormanns D, Diederich S. Characterization of small pulmonary nodules by CT. Eur Radiol 2004:14:1380-91.
8. Swensen SJ, Viggiano RW, Midthun DE, Muller NL, Sherrick A, Yamashita K, et al. Lung nodule enhancement at CT: a multicenter study. Radiology 2000;214:73-80.
9. Wormanns D, Klotz E, Dregger U, Beyer F, Heindel W. Diagnostic performance of different measurement methods for lung nodule enhancement at dynamic computed tomography. Proc. SPIE Medical Imaging Conference 2004. SPIE 2004;5372:455-62.
10. Li F, Li Q, Aoyama M, Shiraishi J, Abe H, Suzuki K, et al. Usefulness of computerized scheme for differentiating benign from malignant lung nodules on high-resolution CT. In: Proceedings of Computer Assisted Radiology and Surgery CARS 2004. Amsterdam. The Netherlands: Elsevier, 2004:946-51.
11. Preteux F, Merlet N, Grenier P, Mouellhi M. Algorithms for automated evaluation of pulmonary lesions by high resolution CT via image analysis. In: Proceedings of Radiological Society of North America RSNA'89. Oak Brook, IL: Radiological Society of North America. 1989:416.
12. Preteux F. A non-stationary Markovian modeling for the lung nodule detection in CT. In: Proceedings of Computer Assisted Radiology CAR 1991. Berlin, Heidelberg, New York: Springer Publishers, 1991:199-204.
13. Giger M, Bae K, MacMahon H. Computerized detection of pulmonary nodules in computed tomography images. Invest Radiol 1994;29:459-65.
14. Lee Y, Hara T, Fujita H, Itoh S, Ishigaki T. Nodule detection on chest helical CT scans by using a genetic algorithm. Proc Intel Inf Systems 1997;67-70.
15. Lee Y, Hara T, Fujita H, Itoh S, Ishigaki T. Automated detection of pulmonary nodules in helical CT images based on an improved template-matching technique. IEEE Trans Medical Imaging 2001;20:595-604.
16. Fiebich M, Wietholt C, Renger B, Armato S, Hoffmann K, Wormanns D, et al. Automatic detection of pulmonary nodules in low-dose screening thoracic CT examinations. In: Proceedings of SPIE Medical Imaging Conference 1999. SPIE 1999;3661:1434-9.
17. Fiebich M, Wormanns D, Heindel W. Improvement of method for computer-assisted detection of pulmonary nodules in CT of the chest. In: Proceedings of SPIE Medical Imaging Conference 2001. SPIE 2001;4322:702-9.
18. Armato S, Giger M, Moran C, Blackburn J, Doi K, MacMahon H. Computerized detection of pulmonary nodules on CT scans. Radiographics 1999:19:1303-11.
19. Armato S, Giger M, Blackburn J, Doi K, MacMahon H. Three-dimensional approach to lung nodule detection in helical CT. In: Proceedings of SPIE Medical Imaging Conference 1999. SPIE 1999;3661:553-9.
20. Armato S, Giger M, MacMahon H. Analysis of a three-dimensional lung nodule detection method for thoracic CT scans. In: Proceedings of SPIE Medical Imaging Conference 2000. SPIE 2000;3979:103-9.
21. Satoh Y, Ukai N, Niki K, Eguchi K, Mori H, Ohmatsu R, et al. Computer aided diagnosis system for lung cancer based on retrospective helical CT image. In: Proceedings of SPIE Medical Imaging Conference 1999. SPIE 1999;3661: 1324-35.
22. Takizawa H, Fukano G, Yamamoto S, Matsumoto T, Tateno Y, Iinuma T, et al. Recognition of lung cancers from X-ray CT images considering 3-D structure of objects and uncertainty of recognition. In: Proceeding of SPIE Medical Imaging Conference 2000. SPIE 2000:3979:998-1007.
23. Reeves A, Kostis W, Yankelewitz D, Henschke C. Three-dimensional shape characterization of solitary pulmonary nodules from helical CT scans. In: Proceedings of Computer Assisted Radiology and Surgery CARS 1999. Amsterdam, The Netherlands: Elsevier, 1999:83-7.
24. Kostis W, Reeves A, Yankelewitz D, Henschke C. Three-dimensional segmentation of solitary pulmonary nodules from helical CT scans. In: Proceedings of Computer Assisted Radiology and Surgery CARS 1999. Amsterdam, The Netherlands: Elsevier, 1999:203-7.
25. Kawata Y, Niki N, Ohmatsu H, Kusumoto M, Kakinuma R, Mori K, et al. Curvature based characterization of shape and internal intensity structure for classification of pulmonary nodules using thin-section CT images. In: Proceedings of SPIE Medical Imaging Conference 1999. SPIE 1999;3661:541-52.
26. Kawata Y, Niki N, Ohmatsu H, Kusumoto M, Kakinuma R, Mori K, et al. Computer aided differential diagnosis of pulmonary nodules based on a hybrid classification approach. In: Proceedings of SPIE Medical Imaging Conference 2001. SPIE 2001;4322:1796-806.
27. McNitt-Gray M, Hart E, Wyckoff N, Sayre J, Goldin J, Aberle A. A pattern classification approach to characterizing solitary pulmonary nodules imaged on high resolution CT: preliminary results. Med Phys 1999;26:880-8.
28. Fan L, Nowak C, Qian J, Kohl G, Naidich D. Automatic detection of lung nodules from multi-slice low-dose CT images. In: Proceedings of SPIE Medical Imaging Conference 2001. SPIE 2001;4322:1828-35.
29. Novak C, Fan L, Qian J, Kohl G, Naidich D. An interactive system for CT lung nodule identification and examination. In: Proceedings of International Conference on Computer Assisted Radiology and Surgery CARS 2001. Amsterdam, The Netherlands: Elsevier, 2001:599-604.
30. Wiemker R, Rogalla P, Zwartkruis A, Blaffert T. Computer aided lung nodule detection on high resolution CT data. In: Proceedings of SPIE Medical Imaging 2002. SPIE 2002;4684:677-88.
31. Novak CL, Qian J, Fan L, Naidich D, Ko JP, Rubinowitz AN. Inter-observer variations on interpretation of multislice CT lung-cancer screening studies and the implications for computer-aided diagnosis. In: Proceedings of SPIE Medical Imaging Conference 2002. SPIE 2002;4680:68-79.
32. Lawler LP, Wood SA, Pannu HS, Fishman EK. Computer-assisted detection of pulmonary nodules: preliminary observations using a prototype system with multidetector-row CT data sets. J Digit Imaging 2003;16:251-61.
33. Naidich DP, Ko JP, Stoeckel J, Abinanti N, Lu S, Moses D, et al. Computer-aided diagnosis: impact on nodule detection among community level radiologists. A multi-reader study. In: Proceedings of Computer Assisted Radiology and Surgery CARS 2004. Amsterdam, The Netherlands: Elsevier, 2004:902-7.
34. Clarke LP, Croft BY, Staab E. New NCI initiatives in computer aided diagnosis. In: Proceedings of SPIE Medical Imaging Conference 2000. SPIE 2000;3976:370-3.
35. Fischbach F, Knollmann F, Griesshaber V, Freund T, Akkol E, Felix R. Detection of pulmonary nodules by multislice computed tomography: improved detection rate with reduced slice thickness. Eur Radiol 2003;13:2378-83.
36. Zhao B, Yankelevitz D, Reeves A, Henschke C. Two-dimensional multi-criterion segmentation of pulmonary nodules on helical CT-images. Med Phys 1999;26:889-95.
37. Wormanns D, Kohl G, Klotz E, Heindel W, Diederich S. Clinical evaluation of the reproducibility of volume measurements of pulmonary nodules. In: Proceedings of SPIE Medical Imaging 2002. SPIE 2002;4684:316-22.
38. Fan L, Qian J, Odry B, Shen H, Naidich D, Kohl G, et al. Automatic segmentation of pulmonary nodules by using dynamic 3D cross-correlation for interactive CAD systems. In: Proceedings of SPIE Medical Imaging 2002. SPIE 2002;4684:1362-9.
39. Wiemker R, Rogalla P, Hein E, Blaffert T, Rösch P. Computer aided segmentation of pulmonary nodules: automated vasculature cutoff in thick- and thinslice CT. In: Proceedings of Computer Assisted Radiology and Surgery, CARS 2003. Amsterdam, The Netherlands: Elsevier, 2003:965-790.
40. Wiemker R, Zwartkruis A. Optimal thresholding for 3D segmentation of pulmonary nodules in high resolution CT. In: Proceedings of International Conference on Computer Assisted Radiology and Surgery CARS 2001. Amsterdam, The Netherlands: Elsevier Publishers, 2001:653-8.
41. Hay O, Sifri D, Srinivas Y, Wiemker R. Evaluation of automatic volumetric segmentation of lung nodules in standard and low dose CT scans. Annual Meeting of the Radiological Society of North America RSNA 2003.
42. Blaffert T, Wiemker R. Comparison of different follow-up lung registration methods with and without segmentation. In: Proceedings of SPIE Medical Imaging Conference 2004. SPIE 2004;5370:1701-8.
43. Shah E, Blaffert T, Subramanyan K, Durgan J, Pohlman S. Automatic matching of the pulmonary nodules in current and former CT studies: a clinical evaluation. In: Proceedings of Computer Assisted Radiology and Surgery CARS 2004. Amsterdam, The Netherlands: Elsevier, 2004:941-5.
44. Betke M, Hong H, Thomas D, Prince C, Ko JP. Landmark detection in the chest and registration of lung surfaces with an application to nodule registration. Med Image Anal 2003;7:265-81.
45. Shen H, Fan L, Qian J, Odry BL, Novak CL, Naidich DP. Real-time and automatic matching of pulmonary nodules in follow-up multi-slice CT studies. In: Proceedings of the International Conference on Diagnostic Imaging and Analysis; 2002 August 18-20; Shanghai, China. 2002:101-6.