An evaluation of image descriptors combined with clinical data for breast cancer diagnosis

International Journal of Computer Assisted Radiology and Surgery

Volumn 8, Issue 4, 2013, Pages 561-574

  Moura, Daniel C ^a,b   Guevara López, Miguel A ^a  

^a UNIVERSITY OF PORTO   (Portugal)

^b UNIVERSITY OF PORTO   (Portugal)

Author keywords

Breast cancer; Clinical data; Computer aided diagnosis (CADx); Histograms of gradient divergence (HGD); Image descriptors; Machine learning classifiers

Indexed keywords

ARTICLE; BREAST CANCER; BREAST TUMOR; CANCER DIAGNOSIS; CLASSIFIER; COMPUTER ASSISTED DIAGNOSIS; DIGITAL MAMMOGRAPHY; HISTOGRAM; HISTOGRAMS OF GRADIENT DIVERGENCE; HUMAN; IMAGE DISPLAY; MACHINE LEARNING; PRIORITY JOURNAL;

EID: 84880229711     PISSN: 18616410     EISSN: 18616429     Source Type: Journal    
DOI: 10.1007/s11548-013-0838-2     Document Type: Article

References (47)

1. Matheus BR, Schiabel H (2011) Online mammographic images database for development and comparison of CAD schemes. J Digit Imaging 24(3):500-506. doi: 10.1007/s10278-010-9297-2
2. Moreira IC, Amaral I, Domingues I, Cardoso A, Cardoso MJ, Cardoso JS (2012) INbreast: toward a full-field digital mammographic database. Acad Radiol 19(2):236-248
3. Nelson HD, Tyne K, Naik A, Bougatsos C, Chan BK, Humphrey L (2009) Screening for breast cancer: systematic evidence review update for the US Preventive Services Task Force. Ann Intern Med 151(10):727
4. Tabar L, Vitak B, Chen THH, Yen AMF, Cohen A, Tot T, Chiu SYH, Chen SLS, Fann JCY, Rosell J, Fohlin H, Smith RA, Duffy SW (2011) Swedish two-county trial: impact of mammographic screening on breast cancer mortality during 3 decades. Radiology 260(3):658-663. doi: 10.1148/radiol.11110469
5. Ramos-Pollán R, Guevara-López M, Suárez-Ortega C, Díaz-Herrero G, Franco-Valiente J, Rubio-del-Solar M, de Posada González N, Vaz M, Loureiro J, Ramos I (2011) Discovering mammography-based machine learning classifiers for breast cancer diagnosis. J Med Syst 1:11. doi: 10.1007/s10916-011-9693-2
6. Warren Burhenne LJ, Wood SA, D'Orsi CJ, Feig SA, Kopans DB, O'Shaughnessy KF, Sickles EA, Tabar L, Vyborny CJ, Castellino RA (2000) Potential contribution of computer-aided detection to the sensitivity of screening mammography. Radiology 215(2):554-562 (Pubitemid 30237859)
7. Cheng HD, Cai X, Chen X, Hu L, Lou X (2003) Computer-aided detection and classification of microcalcifications in mammograms: a survey. Pattern Recogn 36(12):2967-2991. doi: 10.1016/s0031-3203(03)00192-4 (Pubitemid 37293407)
8. Cheng HD, Shi XJ, Min R, Hu LM, Cai XP, Du HN (2006) Approaches for automated detection and classification of masses in mammograms. Pattern Recogn 39(4):646-668. doi: 10.1016/j.patcog.2005.07.006 (Pubitemid 43199461)
9. Christoyianni I, Dermatas E, Kokkinakis G (2000) Fast detection of masses in computer-aided mammography. IEEE Signal Proc Mag 17(1):54-64 (Pubitemid 30549133)
10. Huo ZM, Giger ML, Vyborny C, Wolverton DE, Schmidt RA, Doi K (1998) Automated computerized classification of malignant and benign masses on digitized mammograms. Acad Radiol 5(3):155-168 (Pubitemid 28372697)
11. Constantinidis AS, Fairhurst MC, Rahman AFR (2001) A new multi-expert decision combination algorithm and its application to the detection of circumscribed masses in digital mammograms. Pattern Recogn 34(8):1527-1537 (Pubitemid 32541335)
12. Belkasim SO, Shridhar M, Ahmadi M (1991) Pattern-recognition with moment invariants - a comparative-study and new results. Pattern Recogn 24(12):1117-1138
13. Yu SY, Guan L (2000) A CAD system for the automatic detection of clustered microcalcifications in digitized mammogram films. IEEE Trans Med Imaging 19(2):115-126 (Pubitemid 30594809)
14. Dhawan AP, Chitre Y, KaiserBonasso C, Moskowitz M (1996) Analysis of mammographic microcalcifications using gray-level image structure features. IEEE Trans Med Imaging 15(3): 246-259 (Pubitemid 126780316)
15. Wang D, Shi L, Ann Heng P (2009) Automatic detection of breast cancers in mammograms using structured support vector machines. Neurocomputing 72(13-15):3296-3302. doi: 10.1016/j.neucom.2009.02.015
16. Dua S, Singh H, Thompson HW (2009) Associative classification of mammograms using weighted rules. Expert Syst Appl 36(5):9250-9259. doi: 10.1016/j.eswa.2008.12.050
17. Sahiner B, Chan HP, Petrick N, Helvie MA, Hadjiiski LM (2001) Improvement of mammographic mass characterization using spiculation measures and morphological features. Med Phys 28(7):1455-1465. doi: 10.1118/1.1381548 (Pubitemid 32667287)
18. Sahiner B, Chan HP, Petrick N, Helvie MA, Goodsitt MM (1998) Computerized characterization of masses on mammograms: the rubber band straightening transform and texture analysis. Med Phys 25(4):516-526 (Pubitemid 28178360)
19. Sahiner B, Chan HP, Petrick N, Wei DT, Helvie MA, Adler DD, Goodsitt MM (1996) Classification of mass and normal breast tissue: a convolution neural network classifier with spatial domain and texture images. IEEE Trans Med Imaging 15(5):598-610 (Pubitemid 126780349)
20. Haralick RM, Shanmuga K, Dinstein I (1973) Textural features for image classification. IEEE T Syst Man Cyb 3(6):610-621
21. Kim JK, Park HW (1999) Statistical textural features for detection of microcalcifications in digitized mammograms. IEEE Trans Med Imaging 18(3):231-238
22. Buciu I, Gacsadi A (2010) Directional features for automatic tumor classification of mammogram images. Biomed Signal Process Control 6(4):370-378
23. Ferreira CBR, DbL Borges (2003) Analysis of mammogram classification using a wavelet transform decomposition. Pattern Recogn Lett 24(7):973-982. doi: 10.1016/s0167-8655(02)00221-0 (Pubitemid 36053305)
24. Rashed EA, Ismail IA, Zaki SI (2007) Multiresolution mammogram analysis in multilevel decomposition. Pattern Recogn Lett 28(2):286-292. doi: 10.1016/j.patrec.2006.07.010 (Pubitemid 44716412)
25. Dhawan AP, Chitre Y, Kaiser-Bonasso C (1996) Analysis of mammographic microcalcifications using gray-level image structure features. IEEE Trans Med Imaging 15(3):246-259 (Pubitemid 126780316)
26. Soltanian-Zadeh H, Rafiee-Rad F, Pourabdollah-Nejad DS (2004) Comparison of multiwavelet, wavelet, Haralick, and shape features for microcalcification classification in mammograms. Pattern Recogn 37(10):1973-1986. doi: 10.1016/j.patcog.2003.03.001
27. Meselhy Eltoukhy M, Faye I, Belhaouari Samir B (2010) A comparison of wavelet and curvelet for breast cancer diagnosis in digital mammogram. Comput Biol Med 40(4):384-391. doi: 10.1016/j.compbiomed.2010.02.002
28. Dalal N, Triggs B (2005) Histograms of oriented gradients for human detection. In: IEEE computer society conference on computer vision and, pattern recognition, vol 881, pp 886-893. doi: 10.1109/cvpr.2005.177 (Pubitemid 43897286)
29. Heath M, Bowyer K, Kopans D, Moore R, Kegelmeyer P (2000.) The digital database for screening mammography. In: Proceedings of the 5th international workshop on digital mammography, pp 212-218
30. Ramos Pollán R, Rubio del Solar M, Franco Valiente JM, Moriche JE, Gonzalez de Posada N, Valdes Torres JA, Pires Vaz MA, Guevara López MA (2010) Exploiting e-infrastructures for medical image storage and analysis: a grid application for mammography CAD. In: Hierlemann A (ed) Proceedings of the 7th IASTED international conference on, biomedical engineering
31. de Oliveira JEE, Machado AMC, Chavez GC, Lopes APB, Deserno TM (2010) MammoSys: a content-based image retrieval system using breast density patterns. Comput Methods Programs Biomed 99(3):289-297. doi: 10.1016/j.cmpb.2010.01.005
32. Oliveira JEE, Gueld MO, Araújo AA, Ott B, Deserno TM (2008) Towards a standard reference database for computer-aided mammography. In: Proceedings SPIE 6915, medical imaging 2008: computer-aided diagnosis, 69151Y, pp 1Y1-1Y9. doi: 10.1117/12.770325 (Pubitemid 351747629)
33. Gonzalez RC, Woods RE, Eddins SL (2004) Digital image processing. Prentice Hall, New Jersey
34. Sheshadri HS, Kandaswamy A (2007) Experimental investigation on breast tissue classification based on statistical feature extraction of mammograms. Comput Med Imaging Graph 31(1):46-48. doi: 10.1016/j.compmedimag.2006.09.015 (Pubitemid 44879886)
35. Kinoshita S, Azevedo-Marques P, Pereira R Jr, Rodrigues J, Rangayyan R (2007) Content-based retrieval of mammograms using visual features related to breast density patterns. J Digit Imaging 20(2):172-190. doi: 10.1007/s10278-007-9004-0 (Pubitemid 46789152)
36. Hu MK (1962) Visual-pattern recognition by moment invariants. Ire T Inform Theor 8(2):179-187
37. Teague MR (1980) Image-analysis via the general-theory of moments. J Opt Soc Am 70(8):920-930
38. Wei C-H, Chen SY, Liu X (2011) Mammogram retrieval on similar mass lesions. Comput Methods Programs Biomed 106(3):234-248. doi: 10.1016/j.cmpb.2010.09.002
39. Galloway MM (1975) Texture analysis using gray level run lengths. Comput Graph Image Process 4(2):172-179. doi: 10.1016/s0146-664x(75)80008-6
40. Daugman JG (1985) Uncertainty relation for resolution in space, spatial-frequency, and orientation optimized by two-dimensional visual cortical filters. J Opt Soc Am A 2(7):1160-1169
41. Candes EJ, Donoho DL (2004) New tight frames of curvelets and optimal representations of objects with piecewise C2 singularities. Commun Pure Appl Math 57(2):219-266
42. Candes E, Demanet L, Donoho D, Ying L (2006) Fast discrete curvelet transforms. Multiscale Model Simul 5(3):861-899. doi: 10.1137/05064182X (Pubitemid 47381814)
43. Lowe D (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vis 60(2):91-110. doi: 10.1023/b:visi.0000029664.99615.94
44. Deniz O, Bueno G, Salido J, De la Torre F (2011) Face recognition using histograms of oriented gradients. Pattern Recogn Lett 32(12):1598-1603
45. Hall M, Frank E, Holmes G, Pfahringer B, Reutemann P, Witten IH (2009) The WEKA data mining software: an update. SIGKDD Explor 11(1):10-18
46. Demšar J (2006) Statistical comparisons of classifiers over multiple data sets. J Mach Learn Res 7:1-30 (Pubitemid 43022939)
47. Andreadis II, Spyrou GM, Nikita KS (2011) A comparative study of image features for classification of breast microcalcifications. Meas Sci Technol 22(11):114005-114013. doi: 10.1088/0957-0233/22/11/114005