Comparison of breast density assessments based on interactive thresholding and automated fast fuzzy c-means clustering in three-dimensional MR imaging

IFMBE Proceedings

Volumn 25, Issue 4, 2009, Pages 1893-1896

  Ertas, Gokhan ^a   Reed, S ^a   Leach, M O ^a  

^a INSTITUTE OF CANCER RESEARCH   (United Kingdom)

Author keywords

Breast; Density; Fibroglandular tissue; Fuzzy; MRI

Indexed keywords

BIOINFORMATICS; BIOMECHANICS; BIOMEDICAL ENGINEERING; BIOPHYSICS; DENSITY (SPECIFIC GRAVITY); DIAGNOSIS; DISEASES; IMAGE SEGMENTATION; MAGNETIC RESONANCE IMAGING; MEDICAL IMAGE PROCESSING; MEDICAL PHYSICS; SCANNING; TISSUE;

BREAST; DENSITY ESTIMATION; DENSITY ESTIMATION METHODS; DYNAMIC CONTRAST ENHANCED; FIBROGLANDULAR TISSUE; FUZZY; FUZZY C MEANS CLUSTERING; GRADIENT VECTOR FLOW;

IMAGE ENHANCEMENT;

EID: 77950102569     PISSN: 16800737     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-642-03882-2_503     Document Type: Conference Paper

References (22)

1. McTiernan A, Gilligan M, Redmond C (1997) Assessing individual risk for breast cancer: Risky business. J Clin Epidemiol 50:547-556
2. Lalloo F, Varley J, Moran A et al. (2006) BRCA1, BRCA2 and TP53 mutations in very early-onset breast cancer with associated risks to relatives. Eur J Cancer 42:1143-1150
3. Byrne C, Schairer C, Wolfe J et al. (1995) Mammographic features and breast cancer risk: Effects with time, age, and menopause status. J Natl Cancer Inst 87:1622-1629
4. Wang XH, Good WF, Chapman BE et al. (2003) Automated assessment of the composition of breast tissue revealed on tissue-thicknesscorrected mammography. AJR 180:257-262
5. Lee NA, Rusinek H, Weinreb J et al. (1997) Fatty and fibroglandular tissue volumes in the breasts of women 20-83 years old: Comparison of X-ray mammography and computer-assisted MR imaging. AJR 168:501-506
6. Varley JM, McGown G, Thorncroft M et al. (1997) Germ-line mutations of TP53 in Li-Fraumeni families: an extended study of 39 families. Cancer Res 57:3245-3252
7. Kwong A, Rosenberg J, Van den Bosch MA et al. (2007) MRI background enhancement: Its relationship with breast density and breast cancer risk, Journal of Clinical Oncology, ASCO Annual Meeting Proceedings Part I. 25, 2007, pp 1539
8. Poon CS, Bronskill MJ, Henkelman RM et al. (1992) Quantitative magnetic resonance imaging parameters and their relationship to mammographic pattern. J Natl Cancer Inst 84:777-781
9. Graham SJ, Stanchev PL, Lloyd-Smith JO et al. (1995) Changes in fibroglandular volume and water content of breast tissue during the menstrual cycle observed by MR imaging at 1.5 T. J Magn Reson Imag 5:695-701
10. Graham SJ, Bronskill MJ, Byng JW et al. (1996) Quantitative correlation of breast tissue parameters using magnetic resonance and X-ray mammography. Br J Cancer 73:162-168
11. Boston RC, Schnall MD, Sarah A et al. (2005) Estimation of the content of fat and parenchyma in breast tissue using MRI T1 histograms and phantoms. Magn Reson Imaging 23:591-599
12. Xing Y, Yangming O, Englander S et al. (2007) Simultaneous estimation and segmentation of T1 map for breast parenchyma measurement, Proc. of IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2007, pp 332-335
13. J. Wei J, Chan HP, Helvie MA et al. (2004) Correlation between mammographic density and volumetric fibroglandular tissue estimated on breast MR images. Med Phys 31:923-942
14. Leach MO, Boggis CR, Dixon AK et al. (2005) Screening with magnetic resonance imaging and mammography of a UK population at high familial risk of breast cancer: a prospective multicentre cohort study (MARIBS). The Lancet 365:1769-1778
15. Brown J, Buckley D, Coulthard A et al. (2000) Magnetic resonance imaging screening in women at genetic risk of breast cancer: imaging and analysis protocol for the UK multicentre study. Mag Reson Imag 18:765-776
16. Xu C, Prince JL (1998) Snakes, shapes and gradient vector flow. IEEE Trans Med Imaging 7:359-369
17. Khazen M, Warren RM, Boggis CR et al. (2008) A pilot study of compositional analysis of the breast and estimation of breast mammographic density using three-dimensional T1-weighted magnetic resonance imaging. Cancer Epidemiol Biomarkers Prev 17:2268-2274
18. Khazen M, Warren RM, Leach MO (2006) Magnetic resonance imaging of the breast, analysis and review (MRIBview): An image processing tool for structural, compositional, and functional analysis of the breast, and computer-assisted detection (CAD) of breast cancer, Radiological Society of North America scientific assembly and annual meeting program, Oak Brook, IL, 2006, pp 785
19. Brookes JA, Redpath TW, Gilbert FJ et al. (1996) Measurement of spin-lattice relaxation times with FLASH for dynamic MRI of the breast. Br J Radiol 69:206-214
20. Scott DW (1979) On optimal and data-based histograms. Biometrika 66:605-610
21. Kaiser WA, Zeitler E (1989) MR imaging of the breast: fast imaging sequences with and without Gd-DTPA. Preliminary observations. Radiology 170:681-686
22. Song J, Zhao Q, Wang Y et al. (2006) Gain field correction fast fuzzy c-means algorithm for segmenting magnetic resonance images, PRICAI, 2006, pp 1242-1247