DCE-MRI segmentation and motion correction based on active contour model and forward mapping

Proc. - Seventh ACIS Int. Conf. on Software Eng., Artific. Intelligence, Netw., and Parallel/Distributed Comput., SNPD 2006, including Second ACIS Int. Worshop on SAWN 2006

Volumn 2006, Issue , 2006, Pages 208-212

  Wenzhu, Lu ^a   Jianhua, Yao ^b   Chao, Lu ^a   Prindiville, Sheila ^b   Chow, Catherine ^b  

^a TOWSON UNIVERSITY   (United States)

^b NATIONAL INSTITUTES OF HEALTH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DYNAMIC CONTRAST ENHANCED MAGNETIC RESONANCE IMAGING (DCE-MRI); MOTION ARTIFACTS; MOTION CORRECTION;

COMPUTER AIDED DESIGN; CONFORMAL MAPPING; MAGNETIC RESONANCE IMAGING; MATHEMATICAL MODELS; MATHEMATICAL MORPHOLOGY; MOTION COMPENSATION;

IMAGE SEGMENTATION;

EID: 33845596261     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SNPD-SAWN.2006.29     Document Type: Conference Paper

References (13)

1. Imaginis, C., Breast cancer: Statistics on incidence survival, and screening.
2. Lee, N., et al., Fatty and fibroglandular tissue volumes in the breasts of women 20-83 years old: comparison of X-ray mammography and computer-assisted MR imaging. American Journal of Roentgenology, 1997, 168: p. 501-506.
3. Lina Arbach, Breast MRI: Segmentation and classification, http://css.engineering.uiowa.edu/~larbach/2003-01/image_understanding/ Final_Project_report2.pdf
4. Dr.-Ing. Anke Meyer-Base, Computer-Aided Diagnosis in Breast MRI Based on Unsupervised Clustering Techniques, http://www.eng.fsu.edu/ciscor/ CISCOR%20Website%20Materials/Research%20Highlights/Computer- Aided%20Diagnosis%20in%20Breast %20MRI%20Based%20on%20Unsupervised%20Clustering%20Techniques.pdf
5. Sumati Krishnan, Thomas L. Chenevert, Mark A. Helvie, and Frank L. Londy, Linear motion correction in three dimensions applied to dynamic gadolinium enhanced breast imaging, American Association of Physicists in Medicine, May 1999
6. Arbach, L., A. Stolpen, and J.M. Reinhardt. Classification of Breast MRI Lesions Using a Backpropagation Neural Network (BNN). in IEEE International Symposium of Biomedical Imaging. 2004.
7. Qiu, Y., et al. Correspondence Recovery in 2_View Mammography. in IEEE International Symposium on Biomedical Imaging. 2004. Washington, DC.
8. Ruiter, N., Registration of X-ray Mammograms and MR Volumes of the Female Breast based on Simulated Mammographic Deformation. 2003, Universität Mannheim.
9. Vedad Hadziavdic, A Comparative Study of Active Contour Models for Boundary Detection in Brain Images.
10. Jianhua Yao, Jo Anne Zujewski, Jennifer Orzano, Sheila Prindiville, Catherine Chow, Classification and Calculation of Breast Fibroglandular Tissue Volume on SPGR Fat Suppressed MRI
11. Kass, M., A. Witkin, and D. Terzopoulos, Snakes: Active Contour Models. International Journal of Computer Vision, 1988: p. 321-331.
12. George Wolberg, Digital Image Warping P214-P222
13. George Wolberg, http://delivery.acm.org/10.1145/80000/74371/p369-wolberg. pdf?key1=74371&key2=6861010411&coll=GUIDE&dl=GUIDE&CFID= 68847355&CFTOKEN=56865856