CAD (computed-aided detection) and CADx (computer aided diagnosis) systems in identifying and characterising lung nodules on chest CT: Overview of research, developments and new prospects

Radiologia Medica

Volumn 115, Issue 3, 2010, Pages 385-402

  Fraioli, F ^a   Serra, G ^a   Passariello, R ^a  

^a SAPIENZA UNIVERSITY OF ROME   (Italy)

Author keywords

CAD; Computed tomography; Lung nodules

Indexed keywords

COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED TOMOGRAPHY; DIFFERENTIAL DIAGNOSIS; HUMAN; LUNG NODULE; LUNG TUMOR; PATHOLOGY; RADIOGRAPHY; REVIEW; THORAX RADIOGRAPHY;

DIAGNOSIS, DIFFERENTIAL; HUMANS; LUNG NEOPLASMS; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; RADIOGRAPHY, THORACIC; SOLITARY PULMONARY NODULE; TOMOGRAPHY, X-RAY COMPUTED;

EID: 77953261305     PISSN: 00338362     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11547-010-0507-2     Document Type: Article

References (46)

1. Austin JH, Muller NL, Friedman PJ et al (1996) Glossary of terms for CT of the lungs: recommendations of the nomenclature committee of the Fleishner Society. Radiology 200:327-331
2. Bethany B (2003) The solitary pulmonary nodule. Chest 123:89-96
3. Yankelevitz DF, Hensche CI (2000) Lung cancer: small solitary pulmonary nodules. Radiol Clin North Am 38:1-9
4. Shaffer K (1997) Radiologic evaluation in lung cancer: diagnosis and staging. Chest 112:235-238
5. Fischbach F, Knollmann F, Griesshaber V et al (2003) Detection of pulmonary nodules by multislice computed tomography: improved detection rate with reduced slice thickness. Eur Radiol 13:2378-2383
6. Midthun DE (2000) Solitary pulmonary nodule: time to think small. Curr Opin Pulm Med 6:364-370
7. Li F, Sone S, Abe H et al (2002) Lung cancers missed at low-dose helical CT screening in a general population: comparison of clinical, histopathologic, and imaging findings. Radiology 225:673-683
8. Henschke CI, McCauley DI, Yankelevitz DF et al (1999) Early lung cancer action project: overall design and findings from baseline screening. Lancet 354:99-105
9. Henschke G (2000) Work-up of the solitary nodule. American college of radiology. ACR Appropriateness Criteria. Radiology 215:607-609
10. Armato SG 3rd, Giger ML, Moran CJ et al (1999) Computerized detection of pulmonary nodules on CT scans. Radiographics 19:1303-1311
11. Awai K. et al (2004) Pulmonary nodules at chest CT: effect of computer aided diagnosis on radiologist's detection performance. Radiology 230:347
12. Beigelman-Aubry et al (2007) Computed-Aided Detection of solid lung nodules on follow-up MDCT screening: evaluation of detection, tracking, and reading time. AJR 189:948-955
13. Bellotti et al (2007) A CAD system for nodule detection in low-dose lung CTs based on region growing and a new active contour model. Med Phys 34 4901-4910
14. Ozekes et al (2008) Nodule detection in a lung region that's segmented with using genetic cellular neural networks and 3D template matching with fuzzy rule based thresholding. Korean J Radiol 9:1-9
15. Beyer et al (2007) Comparison of sensitivity and reading time for the use of computer-aided detection (CAD) of pulmonary nodules at MDCT as concurrent or second reader. Eur Radiol 17:2941-2947
16. White et al (2008) Lung nodule CAD software as second reader: a multi center study Acad Radiol 15:326-333
17. Giger ML, Bae KT, MacMahon H (1994) Computerized detection of pulmonary nodules in computed tomography images. Invest Radiol 29:459-465
18. Gurcan MN, Sahiner B, Petrick N et al (2002) Lung nodule detection on thoracic computed tomography images: preliminary evaluation of a computeraided diagnosis system. Med Phys 29:2552-2558
19. Kim JS, Kim JH, Cho G, Bae KT (2005) Automated detection of pulmonary nodules on CT images: Effect of section thickness and reconstruction interval-Initial results. Radiology 236:295-299
20. Fraioli F, Bertoletti L, Napoli A et al (2007) Computer-aided detection (CAD) in lung cancer screening at chest MDCT ROC analysis of CAD versus radiologist performance. J Thorac Imaging 22:241-246
21. Rubin GD, Lyo JK, Paik DS et al (2005) Pulmonary nodules on multidetector row CT scans: performance comparison of radiologists and computer-aided detection. Radiology 234:274-283
22. Das M, Mühlenbruch G, Heinen S et al (2008) Performance evaluation of a computer-aided detection algorithm for solid pulmonary nodules in low-dose and standard-dose MDCT chest examinations and its influence on radiologist. Br J Radiol 81:841-847
23. International Early Lung Cancer Action Program Investigators (2007) Computed tomographic screening for lung cancer: individualising the benefit of the screening. Eur Respir J 30:843-847
24. Wormanns D, Kohl G, Klotz E et al (2004) Volumetric measurements of pulmonary nodules at multi-row detector CT: in vivo reproducibility. Eur Radiol 14:86-92
25. Marten K, Engelke C (2007) Computer-aided detection and automated CT volumetry of pulmonary nodules. Eur Radiol 17:888-901
26. Marten K, Auer F, Schmidt S et al (2006) Inadequacy of manual measurements compared to automated CT volumetry in assessment of treatment response of pulmonary metastases. Eur Radiol 16:781-790
27. Hopper KD, Kasales CJ, Van Slyke MA et al (1996) Analysis of interobserever and intraobserver variability in CT tumor measurements. AJR Am J Roentgenol 167:851-854
28. Fraioli F, Bertoletti L, Napoli A et al (2006) Volumetric evaluation of therapy response in patients with lung metastases. Preliminary results with a computer system (CAD) and comparison with unidimensional measurements. Radiol Med 111:365-375
29. Larici AR, Storto ML, Torge M et al (2008) Automated volumetry of pulmonary nodules on multidetector CT: influence of slice thickness, reconstruction algorithm and tube corrent. Preliminary results. Radiol Med 113:29-42
30. Goo JM, Kim KG, Gierada DS et al (2006) Volumetric measurements of lung nodules with multi-detector row CT: effect of changes in lung volume. Korean J Radiol 7:243-248
31. Doi K (2007) Computer-aided diagnosis in medical imaging: Historical review, current status and future potential. Comput Med Imaging Graph 31:198-211
32. Goldin JG, Brown MS, Petkovska I (2008) Computer-aided diagnosis in lung nodule assessment. J Thorac Imaging 23:97-104
33. Li F, Aoyama M, Shiraishi J et al (2004) Radiologists' performance for differentiating benign from malignant lung nodules on high-resolution CT using computer-estimated likelihood of malignancy. AJR Am J Roentgenol 183:1209-1215
34. Shah SK, McNitt-Gray MF, Rogers SR et al (2005) Computer aided characterization of the solitary pulmonary nodule using volumetric and contrast enhancement features. Acad Radiol 12:1310-1319
35. Passe TJ, Bluemke DA, Siegelman SS (1997) Tumor angiogenesis: tutorial on implications for imaging. Radiology 203:593-600
36. Tateishi U, Kusumoto M, Nishihara H et al (2002) Contrast-enhanced dynamic computed tomography for the evaluation of tumor angiogenesis in patients with lung carcinoma. Cancer 95:835-842
37. Mori K, Niki N, Kondo T et al (2005) Development of a novel computeraided diagnosis system for automatic discrimination of malignant from benign solitary pulmonary nodules on thin-section dynamic computed tomography. J Comput Assist Tomogr 29:215-222
38. Nakamura K, Yoshida H, Engelmann R et al (2000) Computerized analysis of the likelihood of malignancy in solitary pulmonary nodules with use of artificial neural networks. Radiology 214:823-830
39. Gurney JW, Swensen SJ (1995) Solitary pulmonary nodules: determining the likelihood of malignancy with neural network analysis. Radiology 196:823-829
40. Henschke CI, Yankelevitz DF, Mateescu I et al (1997) Neural networks for the analysis of small pulmonary nodules. Clin Imaging 21:390-399
41. Buscema M (1997) A general presentation of artificial neural networks. I. Subst Use Misuse 32:97-112
42. Chen H, Wang XH, Ma DQ, Ma BR (2007) Neural network-based computer-aided diagnosis in distinguishing malignant from benign solitary pulmonary nodules by computed tomography. Chin Med J (Engl) 120:1211-1215
43. Gaeta M, Blandino A, Scrivano E et al (1999) Computer tomography halo sign in pulmonary nodules: frequency and diagnostic value. J Thorac Imaging 14:109-113
44. Buscema M et al (xxxx) Images as Active Connection Matrixes: the J-Net system. IC-MED 1:187
45. M. Buscema, L. Catzola, E. Grossi (2007) Images as active connection matrixes: the JNet System in International Journal of Intelligent Computing in Medical Sciences and Image Processing Vol I. No 3, Issue 1
46. Fraioli F, Bertoletti L, Mennini ML et al (2008) Applicazione clinica di un sistema di intelligenza artificiale applicato per la caratterizzazione automatica dei noduli polmonari basato su sistemi attivi di matrici neurali. SIRM, 43° Congresso Nazionale, 2008