Technique for preprocessing of digital mammogram

Computer Methods and Programs in Biomedicine

Volumn 107, Issue 2, 2012, Pages 175-188

  Maitra, Indra Kanta ^a   Nag, Sanjay ^a   Bandyopadhyay, Samir Kumar ^a  

^a UNIVERSITY OF CALCUTTA   (India)

Author keywords

Contrast limited adaptive histogram equalization (CLAHE); Edge shadowing effect and pectoral muscle; Mammogram; Noise; Region of interest (ROI); Seeded region growing (SRG)

Indexed keywords

ADAPTIVE HISTOGRAM EQUALIZATION; MAMMOGRAM; NOISE; PECTORAL MUSCLES; REGION OF INTEREST; SEEDED REGION GROWING;

ALGORITHMS; GRAPHIC METHODS; IMAGE SEGMENTATION; MAMMOGRAPHY; MUSCLE;

X RAY SCREENS;

ACCURACY; ADIPOSE TISSUE; ALGORITHM; ARTICLE; CONTRAST ENHANCEMENT; CONTRAST LIMITED ADAPTIVE HISTOGRAM EQUALIZATION; DIAGNOSTIC IMAGING; DIGITAL MAMMOGRAPHY; FALSE NEGATIVE RESULT; FALSE POSITIVE RESULT; HISTOGRAM; HUMAN; IMAGE ANALYSIS; IMAGE PROCESSING; IMAGE QUALITY; PECTORAL MUSCLE; PROBABILITY; RADIOLOGICAL PARAMETERS; REGION OF INTEREST; THORAX WALL;

ALGORITHMS; BREAST NEOPLASMS; FEMALE; HUMANS; MAMMOGRAPHY; MODELS, BIOLOGICAL; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

EID: 84861994816     PISSN: 01692607     EISSN: 18727565     Source Type: Journal    
DOI: 10.1016/j.cmpb.2011.05.007     Document Type: Article

References (36)

1. Breast Cancer Facts Figures, 2009-2010, American Cancer Society, Inc.
2. Norum J. Breast cancer screening by mammography in Norway. Is it cost-effective?. Ann. Oncol. 1999, 10:197-203.
3. Michaelson J., Satija S., Moore R., et al. The pattern of breast cancer screening utilization and its consequences. Cancer 2002, 94(January (1)):37-43.
4. Baines C.J., McFarlane D.V., Miller A.B. The role of the reference radiologist: estimates of interobserver agreement and potential delay in cancer detection in the national screening study. Invest. Radiol. 1990, 25:971-976.
5. Wallis M.G., Walsh M.T., Lee J.R. A review of false negative mammography in a symptomatic population. Clin. Radiol. 1991, 44:13-15.
6. Sterns E.E. Relation between clinical and mammographic diagnosis of breast problems and the cancer/biopsy rate. Can. J. Surg. 1996, 39(2):128-132.
7. Highnam R., Brady M. Mammographic Image Analysis 1999, Kluwer Academic Publishers, ISBN 0-7923r-r5620-9.
8. Kekre H.B., Sarode Tanuja K., Gharge Saylee M. Tumor detection in mammography images using vector quantization technique. Int. J. Intell. Inform. Technol. Appl. 2009, 2(5):237-242.
9. FDA Web site, http://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfMQSA/mqsa.cfm.
10. National Cancer Institute (NCI) Web site, http://www.cancernet.gov/.
11. Suckling J., Parker J., Dance D.R., Astley S., Hutt I., Boggis C.R.M., Ricketts I., Stamatakis E., Cernaez N., Kok S.L., Taylor P., Betal D., Savage J. The mammographic image analysis society digital mammogram database. Proceedings of the 2nd International Workshop on Digital Mammography 1994, 375-378. Elsevier Science, Amsterdam, The Netherlands.
12. Heath M., Bowyer K., Kopans D., Moore R., Kegelmeyer P. The digital database for screening mammography. Proceedings of the 5th International Workshop on Digital Mammography 2001, 212-218. Medical Physics Publishing.
13. Sanmeet Bawa, A thesis on "Edge Based Region Growing", Department of Electronics and communication Engimeering, Thapar Institute of Engineering & Technology (Deemed University), India, June 2006.
14. Besl P.J., Jain R.C. Segmentation through variable-order surface fitting. IEEE Trans. Pattern Anal. Mach. Intell. 1988, PAMI-IO:167-192.
15. Haralick R.M., Shapiro L.G. Image segmentation techniques. Comput. Vis. Graph. Image Process. 1985, 29:100-132.
16. Sahoo P.K., Soltani S., Wong A.K.C. A survey of thresholding techniques. Comput. Vis. Graph. Image Process. 1988, 41:233-260.
17. Davis L.S. A survey of edge detection techniques. Comput. Graph. Image Process. 1975, 4:248-270.
18. Zucker S.W. Region growing: childhood and adolescence. Comput. Graph. Image Process. 1976, 5:382-399.
19. Horowitz S.L., Pavlidis T. Picture segmentation by a directed split-and-merge procedure. Proc. 2nd Int. Joint Conf. Pattern Recognit. 1974, 424-433.
20. Meyer F., Beucher S. Morphological segmentation. J. Vis. Commun. Image Represent. 1990, 1:2146.
21. Rolf Adams, et al. Seeded region growing. IEEE Trans. Pattern Anal. Mach. Intell. 1994, 16(June (6)):641-647.
22. Mehnert, Jackway P An improved seeded region growing algorithm. Pattern Recogn. Lett. 1997, 18:1065-1071.
23. Beaulieu J.M., Goldberg M. A hierarchy research article in picture segmentation: a stepwise optimisation approach. IEEE Trans. Pattern Anal. Mach. Intell. 1989, 11(2):150-163.
24. Gambotto J.P. A new approach to combining region growing and edge detection. Pattern Recogn. Lett. 1993, 14:869-875.
25. S.A. Hojjatoleslami, J. Kittler, Region growing: a new approach, Dept. Electric. Electronics Engg., Univ. Surrey, Guildford, UK, GU25XH, 2002.
26. R.C., Gonzalez, R.E. Woods, Digital image processing, 1992.
27. Pizer S.M. Psychovisual issues in the display of medical images. Pictoral Information Systems in Medicine 1985, 211-234. Springer-Verlag, Berlin, Germany. K.H. Hoehne (Ed.).
28. Pisano E.D., et al. Contrast limited adaptive histogram equalization image processing to improve the detection of simulated speculations in dense mammograms. J. Digital Imaging 1998, 11(4):193-200.
29. Wanga X., Wong B.S., Guan T.C. Image enhancement for radiography inspection. Int. Conf. Exp. Mech. 2004, 462-468.
30. Ball J.E. Digital mammogram spiculated mass detection and spicule segmentation using level sets. Proceedings of the 29th Annual International Conference of the IEEE EMBS 2007, 4979-4984.
31. Daskalakis Antonis, et al. An efficient CLAHE-based, spot-adaptive, image segmentation technique for improving microarray genes' quantification. 2nd International Conference on Experiments/Process/System Modelling/Simulation and Optimization 2007.
32. Wirth M., Nikitenko D., Lyon J. Segmentation of the breast region in mammograms using a rule-based fuzzy reasoning algorithm. ICGST-GVIP J. 2005, 5(2):45-54.
33. Mario Mustra, Jelena Bozek, Mislav Grgic, Breast Border Extraction and Pectoral Muscle Detection using Wavelet Decomposition, EUROCON 2009, IEEE, St. Petersburg, pp 1426-1433.
34. David Raba, Arnau Oliver, Joan Martói, Marta Peracaula, Joan Espunya Breast Segmentation with Pectoral Muscle Suppression on Digital Mammograms 2005, Springer-Verlag, Berlin Heidelberg, 471-478, LNCS 3523.
35. Zhili Chen and Reyer Zwiggelaar," Segmentation of the Breast Region with Pectoral Muscle Removal in Mammograms", Medical Image Understanding and Analysis (MIUA) 2010, The University of Warwick, Coventry, UK, pp 71-76.
36. Sultana Alina, Ciuc Mihai, Strungaru Rodica Detection of pectoral muscle in mammograms using a mean-shift segmentation approach, communications (COMM). 2010 8th International Conference 2010, 165-168.