GPCALMA: Implementation in Italian hospitals of a computer aided detection system for breast lesions by mammography examination

Physica Medica

Volumn 25, Issue 2, 2009, Pages 58-72

  Lauria, Adele ^a  

^a UNIVERSITY OF NAPLES FEDERICO II   (Italy)

Author keywords

CAD; GRID; Mammography; Neural network

Indexed keywords

ARTICLE; BREAST LESION; COMPUTER AIDED DESIGN; HUMAN; IMAGE ANALYSIS; MAMMOGRAPHY; RADIOLOGIST; SENSITIVITY ANALYSIS; X RAY;

ADULT; AGED; AGED, 80 AND OVER; ALGORITHMS; ARTIFICIAL INTELLIGENCE; BREAST NEOPLASMS; DATABASE MANAGEMENT SYSTEMS; EQUIPMENT DESIGN; EQUIPMENT FAILURE ANALYSIS; FEMALE; HUMANS; INFORMATION STORAGE AND RETRIEVAL; ITALY; MAMMOGRAPHY; MIDDLE AGED; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; RADIOLOGY INFORMATION SYSTEMS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; YOUNG ADULT;

EID: 67349269614     PISSN: 11201797     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ejmp.2008.05.002     Document Type: Article

References (59)

1. Bray F., McCarron P., and Maxwell Parkin D. The changing global patterns of female breast cancer incidence and mortality. Breast Cancer Res 6 (2004) 229-239
2. Levi F., Lucchini F., Negri E., and La Vecchia C. Trends in mortality from major cancers in the European Union, including acceding countries, in 2004. Cancer 101 (2004) 2843-2850
3. Thurfjell E., Anders Lernevall K., and Taube A. Benefit of independent double reading in a population-based mammography screening program. Radiology 191 (1994) 241-244
4. Anttinen I., Pamilo M., Soiva M., and Roiha M. Double reading of mammography screening films-one radiologist or two?. Clin Radiol 48 (1993) 414-421
5. Freer W.T., and Ulissey M.J. Screening mammography with computer-aided detection: prospective study of 12,860 patients in a community breast center. Radiology 220 (2001) 781-786
6. Brake G.M., Karssemeijer N., and Hendriks J.H.C.L. Automated detection of breast carcinomas not detected in a screening program. Radiology 207 (1998) 465-471
7. Ciatto S., Rosselli Del Turco M., Risso G., Catarzi S., Bonardi R., Viterbo V., et al. Comparison of standard reading and computer aided detection (CAD) on a national proficiency test of screening mammography. Eur J Radiol 45 (2003) 135-138
8. Georgian-Smith D., Moore R.H., Halpern E., Yeh E.D., Rafferty E.A., D'Alessandro H.A., et al. Blinded comparison of computer-aided detection with human second reading in screening mammography. Am J Roentgenol 189 5 (2007) 1135-1141
9. Nishikawa R.M., and Kallergi M. Computer-aided detection, in its present form, is not an effective aid for screening mammography. Med Phys 33 (2006) 811-814
10. Bazzocchi M., Mozzarella F., Del Frate C., Girometti F., and Zuiani C. CAD systems for mammography: a real opportunity? A review of the literature. La Radiol Med 112 (2007)
11. Lauria A., Palmiero R., Forni G., Cerello P., Golosio B., Fauci F., et al. The CALMA system: an artificial neural network method for detecting masses and microcalcifications in digitized mammograms. Nucl Instrum Meth A 518 (2004) 391-393
12. Lauria A., Palmiero R., Forni G., Fantacci M.E., Imbraco M., Sodano A., et al. A study on two different CAD systems for mammography as an aid to radiological diagnosis in the search of microcalcification clusters. Eur J Radiol 55 2 (2005) 264-269
13. Bagnasco S., Bottigli U., Cerello P., Delogu P., Fantacci M.E., Lopez Torres E., et al. GPCALMA: a grid approach to mammographic screening. Nucl Instrum Meth A 518 (2004) 394-398
14. Fauci F., Raso G., Magro R., Forni G., Lauria A., Bagnasco S., et al. A massive lesion detection algorithm in mammography. Phys Medica xxi (2005) 21-28
15. Bellotti R., De Carlo F., Tangaro S., Gargano G., Maggipinto G., Castellano M., et al. A completely automated CAD system for mass detection in a large mammographic database. Med Phys 33 (2006) 3066-3075
16. Osuch J.R., Anthony M., Bassett L.W., DeBor M., D'Orsi C., Hendrick R.E., et al. A proposal for a national mammography database: content, purpose, and value. Am J Roentgenol 164 (1995) 1329-1334
17. Nunes FLS, Schiabel H, Rodrigo H, Benatti RH. A computer system to record and retrieve information from a mammographic images database by internet. World Congress on Medical Physics and Biomedical Engineering, 25-31 August 2003, Sydney, Australia.
18. McClatchey R, Manset D, Hauer T, Estrella F, Saiz P, Rogulin D, et al. The MammoGrid project grids architecture. Computing in High Energy and Nuclear Physics (CHEP03) La Jolla, Ca, USA, March 2003.
19. Ertas G, Gulcur HÖ, Aribal E, Semiz A. Development of a secure mammogram database. MEDNET 2001: abstract no. 54.
20. Computer aided detection in mammography. NHS Breast Screening Programme Publication No. 48; 2001.
21. Bazzocchi M., Facecchia I., Zuiani C., Londero V., Smania S., Bottigli U., et al. Application of a computer-aided detection (CAD) system to digitalized mammograms for identifying microcalcifications. Radiol Med 101 (2001) 334-340
22. James J.J. The current status of digital mammography. Clin Radiol 59 (2004) 1-10
23. Jong R.A., Yaffe M.J., Skarpathiotakis M., Shumak R.S., Danjoux N.M., Gunesekara A., et al. Contrast-enhanced digital mammography: initial clinical experience. Radiology 228 (2003) 842-850
24. Kim S.J., Moon W.K., Cho N., Cha J.H., Kim S.M., and Im J.G. Computer-aided detection in full-field digital mammography: sensitivity and reproducibility in serial examinations. Radiology 246 (2008) 71-80
25. Boone J.M., Gross G.W., and Greco-Hunt V. Neural networks in radiologic diagnosis I. Introduction and illustration. Invest Radiol 25 (1990) 1012-1016
26. D'Orsi C.J. Computer-aided detection: there is no free lunch. Radiology 221 (2001) 585-586
27. Huo Z., Giger M.L., and Metz C.E. Effect of dominant features on neural network performance in the classification of mammographic lesions. Phys Med Biol 44 (1999) 2579-2595
28. te Brake G.M., Karssemeijer N., and Hendriks J.H.C.L. An automatic method to discriminate malignant masses from normal tissue in digital mammograms. Phys Med Biol 45 (2000) 2843-2857
29. Woods K., and Bowyer K.W. Generating ROC curves for artificial neural networks. IEEE Trans Med Imaging 16 (1997) 329-337
30. Chan H., Wei D., Helvie M.A., Sahiner B., AdIer D.D., Goodsitt M.M., et al. Computer-aided classification of mammographic masses and normal tissue: linear discriminant analysis in texture feature space. Phys Med Biol 40 (1995) 857-876
31. Gupta R., and Undrill P.E. The use of texture analysis to delineate suspicious masses in mammography. Phys Med Biol 40 (1995) 835-855
32. Catarious D.M., Baydush A.H., and Floyd Jr. C.E. Incorporation of an iterative, linear segmentation routine into a mammographic mass CAD system. Med Phys 31 (2004) 1512-1520
33. Haralik R.M., Shanmugan K., and Dinstein I. Textural features for image classification. IEEE Trans Syst Man Cybernet 3 (1973) 610-621
34. Conners R.W., and Harlow C.A. A theoretical comparison of texture algorithms. IEEE Trans Pattern Anal Machine Intell 2 (1980) 204-222
35. Hertz J., Krogh A., and Palmer R.G. Introduction to the theory of neural computation (1991), Addison-Wesley
36. Stone M. Cross-validatory choice and assessment of statistical predictions. J Roy Stat Soc B 36 1 (1974) 111-147
37. Chakraborty D.P., and Winter L.H.L. Free-response methodology: alternate analysis and a new observer-performance experiment. Radiology 174 3I (1990) 873-881
38. Cheng H.D., Cai X., Chen X., Hu L., and Lou X. Computer-aided detection and classification of microcalcifications in mammograms: a survey. Pattern Recogn 36 (2003) 2967-2991
39. Gavrielides M.A., Lo J.Y., and Floyd Jr. C.E. Parameter optimization of a computer-aided diagnosis scheme for the segmentation of microcalcification clusters in mammograms. Med Phys 29 (2002) 475-483
40. Kallergi M. Computer-aided diagnosis of mammographic microcalcification clusters. Med Phys 31 (2004) 314-316
41. Chan H., Sahiner B., Lam K.L., Petrick N., Helvie M.A., Goodsitt M.M., et al. Computerized analysis of mammographic microcalcifications in morphological and texture feature spaces. Med Phys 25 (1998) 2007-2019
42. Veldkamp W., Karssemeijer N., Otten J., and Hendriks J. Automated classification of clustered microcalcifications into malignant and benign types. Med Phys 27 (2000) 2600-2608
43. Gurcan M.N., Chan H.P., Sahiner B., Hadjiiski L., Petrick N., and Helvie M. Optimal neural network architecture selection: improvement in computerized detection of microcalcifications. Acad Radiol 9 (2002) 420-429
44. Fantacci M.E., Bottigli U., Delogu P., Fauci F., Golosio B., Lauria A., et al. Search of microcalcification clusters with the CALMA CAD station. Proc SPIE 4684 (2002) 1301-1310
45. Cheran S.C., Cataldo R., Cerello P., De Carlo F., Fauci F., Forni G., et al. Detection and classification of microcalcification clusters in digitized mammograms. IEEE Nucl Sci Symp Conf Rec 7 (2004) 4136-4140
46. Vincent L. Morphological grayscale reconstruction in image analysis: applications and efficient algorithms. IEEE Trans Image Process 2 (1993) 176-201
47. Lattanzio E., and Guerrieri A.M. The mammography report. Radiol Med 96 (1998) 283-288
48. Green D.N., and Swets J.A. Signal detection theory and psychophysics (1966), John Wiley and Sons, New York
49. Metz C.E. ROC methodology in radiologic imaging. Invest Radiol 21 (1986) 720-733
50. Hanley J.A., and McNeil B.J. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143 (1982) 29-36
51. Bornefalk H. Implications of unchanged detection criteria with CAD as second reader of mammograms. Med Phys 33 (2006) 922-929
52. Bilska-Wolak A.O., and Floyd Jr. C.E. Tolerance to missing data using a likelihood ratio based classifier for computer-aided classification of breast cancer. Phys Med Biol 49 (2004) 4219-4237
53. Campanini R., Dongiovanni D., Iampieri E., Lanconelli N., Masotti M., Palermo G., et al. A novel featureless approach to mass detection in digital mammograms based on support vector machines. Phys Med Biol 49 (2004) 961-975
54. Timp S., and Karssemeijer N. A new 2D segmentation method based on dynamic programming applied to computer aided detection in mammography. Med Phys 31 (2004) 958-971
55. Taylor P., Champness J., Given-Wilson R., Johnston K., and Potts H. Impact of computer-aided detection prompts on the sensitivity and specificity of screening mammography. Health Technol Assess 9 6 (2005)
56. Helvie M., Hadjiiski L., Makariou E., Chan H., Petrick N., Sahiner B., et al. Sensitivity of noncommercial computer-aided detection system for mammographic breast cancer detection: pilot clinical trial. Radiology 231 (2004) 208-214
57. Astley S.M., and Gilbert F.J. Computer-aided detection in mammography. Clin Radiol 59 (2004) 390-399
58. Zheng B., Gur D., Good W.F., and Hardesty L.A. A method to test the reproducibility and to improve performance of computer-aided detection schemes for digitized mammograms. Med Phys 31 (2004) 2964-2972
59. Bagnasco S., Bottigli U., Cerello P., Cheran S., Delogu P., Fantacci M.E., et al. GPCALMA: a grid based tool for mammographic screening. Method Inform Med 44 2 (2005) 244-248