Adaptive segmentation of MR axial brain images using connected components

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2059, Issue , 2001, Pages 295-302

  Biancardi, Alberto ^a   Segovia Martínez, Manuel ^b  

^a UNIVERSITY OF PAVIA   (Italy)

^b UNIVERSITY OF SURREY   (United Kingdom)

Author keywords

Brain segmentation; Connected components; Connected filters; Magnetic resonance imaging (MRI); Medical image analysis

Indexed keywords

BRAIN MAPPING; MAGNETIC RESONANCE IMAGING; MEDICAL IMAGING;

ADAPTIVE SEGMENTATION; BRAIN SEGMENTATION; CONNECTED COMPONENT; CONNECTED FILTERS; MAGNETIC RESONANCE BRAIN IMAGES; PARALLEL PLATFORMS; PIXEL-LEVEL PROCESSING; SEGMENTATION PROCEDURE;

IMAGE SEGMENTATION;

EID: 84896726368     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45129-3_26     Document Type: Conference Paper

References (20)

1. Atkins, M.S., Mackiewich, B.T.: Fully Automatic Segmentation of the Brain in MRI. IEEE Trans. Med. Imag. 17 (1998) 98-107.
2. Bezdek, J.C., Hall, L.O., Clarke, L.P.: Review of MR Image Segmentation Techniques Using Patter Recognition. Medical Physics 20 (1993) 1033-1048.
3. Biancardi, A., Mérigot, A.: Connected component support for image analysis programs. Proc. 13th Inter. Conf. on Pattern Recognition 4 (1996) 620-624.
4. Crespo, J., Maojo, V.: Shape preservation in morphological filtering and segmentation. Proc. XII Brazilian Symposium on Computer Graphics and Image Processing (1999) 247-256.
5. Davatzikos, C.A., Prince, J.L.: An Active Contour Model for Mapping the Cortex. IEEE Trans. Med. Imag. 14 (1995) 65-80.
6. M. J. B. Du, Propagation in Cellular Logic Arrays, Proc. Workshop on Picture Data Description and Management (1980) 259-262.
7. Freeborough, P.A., Fox N.C.: MR Image Texture Analysis Applied to the Diagnosis and Tracking of Alzheimer’s Disease. IEEE Trans. Med. Imag. 17 (1998) 475-479.
8. Freeborough, P.A., Fox N.C., Kitney, R.I.: Interactive Algorithms for the Segmentation and Quantitation of 3D MRI Brain Scans Comp. Meth. Programs in Biomed. 53 (1997) 15-25.
9. Hillis, W. D., Steele Jr., G. L.: Data parallel algorithms. Communications of the ACM 29 12 (1986) 1170-1183.
10. Hohne, K.H., Hanson, W.: Interactive 3D Segmentation of MRI and CT Volumes using Morphological Operations. Journal of Computer Assisted Tomography 16 (1994) 285-294.
11. Kapur, T., Grimson, W.E.L., Wells, W.M., Kikinis, R.: Segmentation of Brain Tissue from Magnetic Resonance Images Med. Imag. Anal. 1 (1996).
12. Kass, M., Witkin, A., Terzopulos, D.: Snakes: Active Contour Models. Intern. Jour. Comput. Vision (1998) 321-331.
13. Lantuéjoul, C.: Geodesic Segmentation in Preston Jr., K., Uhr, L. (eds.): Multicomputers and Image Processing. Academic Press, New York (1982).
14. Mèrigot, A.: Associative nets: A graph-based parallel computing model. IEEE Trans. on Computer 46 (1997) 558-571.
15. Mèrigot, A., Dulac, D., Mohammadi, S.: A new scheme for massively parallel image analysis. Proc. 12th Intern. Conf. on Pattern Recognition 3 (1994) 352-356.
16. Niessen, W.J., Vincken, K.L., Weickert J., Viergrever, M.A.: Three-dimensional MR Brain Segmentation. 6TH Intern. Conf. on Computer Vision (1998) 53-58.
17. Salembier, P., Serra, J.: Flat Zones Filtering, Connected Operators, and Filters by Reconstruction. IEEE Trans. on Image Process. 4 (1995) 1153-1160.
18. Serra, J.: Image Analysis and Mathematical Morphology. Academic Press, New York (1982).
19. Soille, P.: Morphological Image Analysis. Springer-Verlag, Berlin Heidelberg New York (1999).
20. Zijdenbos, A.P., Dawant, B.M., Margolin, R.A., Palmer, A.C.: Morphometric Analysis of White Matter Lesions in MR Images: Method and Validation. IEEE Trans. Med. Imag. 13 (1994) 716-724.