Interactive volume segmentation with differential image foresting transforms

IEEE Transactions on Medical Imaging

Volumn 23, Issue 9, 2004, Pages 1100-1108

  Falcão, Alexandre X ^a   Bergo, Felipe P G ^a  

^a UNIVERSITY OF CAMPINAS   (Brazil)

Author keywords

3 D visualization; Dijkstra's algorithm; Fuzzy connectedness; Graph search algorithms; Image analysis; Image foresting transform; Medical imaging; Minimum cost path forest; User assisted image segmentation; Watershed transform

Indexed keywords

3-D VISUALIZATION; FUZZY CONNECTEDNESS; GRAPH-SEARCH ALGORITHMS; IMAGE FORESTING TRANSFORM (IFT); MINIMUM-COST PATH FOREST; USER-ASSISTED IMAGE SEGMENTATION; WATERSHED TRANSFORMS;

ALGORITHMS; FUZZY CONTROL; GRAPH THEORY; IMAGE ANALYSIS; IMAGE PROCESSING; MEDICAL IMAGING;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; BRAIN; CLINICAL TRIAL; COMPARATIVE STUDY; COMPUTER ASSISTED DIAGNOSIS; COMPUTER GRAPHICS; COMPUTER INTERFACE; COMPUTER PROGRAM; HISTOLOGY; HUMAN; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; ONLINE SYSTEM; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING; VALIDATION STUDY;

ALGORITHMS; BRAIN; COMPUTER GRAPHICS; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; ONLINE SYSTEMS; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SOFTWARE; USER-COMPUTER INTERFACE;

EID: 4444285279     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2004.829335     Document Type: Article

References (31)

1. J. S. Duncan and N. Ayache, "Medical image analysis: Progress over two decades and the challenges ahead," IEEE Trans. Pattern Anal. Machine Intell., vol. 22, pp. 85-105, Jan. 2000.
2. K. H. HÖhne and W. A. Hanson, "Interactive 3D-segmentation of MRI and CT volumes using morphological operations," J. Comput. Assist. Tomogr., vol. 16, no. 2, pp. 285-294, 1992.
3. G. Kühne, C. Poliwoda, C. Reinhart, T. Günther, J. Hesser, and R. Männer, "Interactive segmentation and visualization of volume data sets," presented at the IEEE Visualization 97, Late Breaking Hot Topics, Phoenix, AZ, 1997, pp. 9-12.
4. A. X. Falcão, J. K. Udupa, S. Samarasekera, S. Sharma, B. E. Hirsch, and R. A. Lotufo, "User-steered image segmentation paradigms: Live-wire and live-lane," Graphical Models Image Processing, vol. 60, no. 4, pp. 233-260, July 1998.
5. T. McInerney and D. Terzopoulos, "T-snakes: Topology adaptive snakes," Med. Image Anal., vol. 4, pp. 73-91, 2000.
6. H. G. Schnack, H. E. HulshoffPol, W. F. C. Baaré, M. A. Viergever, and R. S. Kahn, "Automatic segmentation of the ventricular system from MRI images of the human brain," NeuroImage, vol. 14, pp. 95-104, 2001.
7. T. Lei, J. K. Udupa, P. K. Saha, and D. Odhner, "Artery-vein separation via MRA - An image processing approach," IEEE Trans. Med. Imag., vol. 20, Aug. 2001.
8. A. X. Falcão, J. K. Udupa, and F. K. Miyazawa, "An ultra-fast user-steered image segmentation paradigm: Live-wire-on-the-fly," IEEE Trans. Med. Imag., vol. 19, pp. 55-62, Jan. 2000.
9. A. X. Falcão and J. K. Udupa, "A 3D generalization of user-steered live wire segmentation," Med. Imag. Anal. vol. 4, no. 4, pp. 389-402, Dec. 2000.
10. W. E. Higgins and E. J. Ojard, "Interactive morphological watershed analysis for 3D medical images," Computerized Med. Imag. Graphics, vol. 17, no. 4/5, pp. 387-395, 1993.
11. G. Buena, O. Musse, F. Heitz, and J. P. Armspach, "Three-dimensional segmentation of anatomical structures in MR images on large data bases," Magn. Reson. Imag., vol. 19, pp. 73-88, 2001.
12. A. Schenk, G. Prause, and H. O. Peitgen, "Efficient semiautomatic segmentation of 3D objects in medical images," in Lecture Notes in Computer Science. Berlin, Germany: Springer-Verlag, 2000, vol. 1935, pp. 186-195.
13. A. X. Falcão, J. Stolfi, and R. A. Lotufo, "The image foresting transform: Theory, algorithms and applications," IEEE Trans. Pattern Anal. Machine Intell., vol. 26, pp. 19-29, Jan. 2004.
14. R. A. Lotufo and A. X. Falcão, "The ordered queue and the optimality of the watershed approaches," in Mathematical Morphology and Its Applications to Image and Signal Processing. Norwell, MA: Kluwer, June 2000, vol. 18, pp. 341-350.
15. A. X. Falcão, B. S. da Cunha, and R. A. Lotufo, "Design of connected operators using the image foresting transform," Proc. SPIE Med. Imag., vol. 4322, pp. 468-479, Feb. 2001.
16. A. X. Falcão, L. F. Costa, and B. S. da Cunha, "Multiscale skeletons by image foresting transform and its applications to neuromorphometry," Pattern Recognition, vol. 35, no. 7, pp. 1571-1582, Apr. 2002.
17. R. A. Lotufo, A. X. Falcão, and F. Zampirolli, "IFT-watershed from gray-scale marker," in Proc. XV Brazilian Symp. Computer Graphics and Image Processing, Oct. 2002, pp. 146-152.
18. R. S. Torres, A. X. Falcão, and L. F. Costa, "A graph-based approach for multiscale shape analysis," Pattern Recogn., vol. 37, no. 6, pp. 1163-1174, June 2004.
19. L. Vincent and P. Soille, "Watersheds in digital spaces: An efficient algorithm based on immersion simulations," IEEE Trans. Pattern Anal. Machine Intell., vol. 13, June 1991.
20. S. Beucher and F. Meyer, "The morphological approach to segmentation: The watershed transformation," in Mathematical Morphology in Image Processing. New York: Marcel Dekker, 1993, ch. 12, pp. 433-481.
21. J. B. T. M. Roerdink and A. Meijster, "The watershed transform: Definitions, algorithms and parallelization strategies," Fundamenta Informaticae, vol. 41, pp. 187-228, 2000.
22. J. K. Udupa and S. Samarasekera, "Fuzzy connectedness and object definition: Theory, algorithms, and applications in image segmentation," Graphical Models Image Processing, vol. 58, pp. 246-261, 1996.
23. P. K. Saha and J. K. Udupa, "Relative fuzzy connectedness among multiple objects: Theory, algorithms, and applications in image segmentation," Comput. Vis. Image Understanding, vol. 82, pp. 42-56, 2001.
24. L. G. Nyúl, A. X. Falcão, and J. K. Udupa, "Fuzzy-connected 3D image segmentation at interactive speeds," Graphical Models, vol. 64, no. 5, pp. 259-281, 2002.
25. P. Felkel, M. Bruckschwaiger, and R. Wegenkittl, "Implementation and complexity of the watershed-from-markers algorithm computed as a minimal cost forest," Comput. Graphics Forum (Eurographics), vol. 20, no. 3, pp. C26-C35, 2001.
26. A. X. Falcão and F. P. G. Bergo, "The iterative image foresting transform and its application to user-steered 3D segmentation," Proc. SPIE Med. Imag., vol. 5032, pp. 1464-1475, Feb. 2003.
27. F. P. G. Bergo and A. X. Falcão. (2003, July) Interactive 3D Segmentation of Brain MRI with Differential Watersheds. Tech. Rep. IC-03-16 Inst. Computing, Univ. Campinas. Campinas, SP, Brazil. [Online]. Available: http://www.ic.unicamp.br/ic-tr.
28. L. Vincent, "Morphological grayscale reconstruction in image analysis," IEEE Trans. Image Processing, vol. 2. pp. 176-201, Apr. 1993.
29. R. K. Ahuja, T. L. Magnanti, and J. B. Orlin, Network Flows: Theory, Algorithms and Applications. Englewood Cliffs, NJ: Prentice-Hall, 1993.
30. J. M. Gauch, "Image segmentation and analysis via multiscale gradient watershed hierarchies," IEEE Trans. Image Processing, vol. 8, pp. 69-79, Jan. 1999.
31. P. Saha and J. K. Udupa, "Scale-based fuzzy connected image segmentation: Theory, algorithms and validation," Comput. Vis. Image Understanding, vol. 77, no. 2, pp. 145-174, 2000.