Segmentation of liver, its vessels and lesions from CT images for surgical planning

BioMedical Engineering Online

Volumn 10, Issue , 2011, Pages

  Oliveira, Dário A B ^a   Feitosa, Raul Q ^a   Correia, Mauro M ^b  

^a PONTIFICAL CATHOLIC UNIVERSITY OF RIO DE JANEIRO   (Brazil)

^b Department of Surgery   (Brazil)

Author keywords

[No Author keywords available]

Indexed keywords

CANCER TREATMENT; COMPUTER TOMOGRAPHY IMAGES; CT IMAGE; DEFORMABLE MODELS; GAUSSIANS; INTERNAL STRUCTURE; LEVEL SET; LIVER SEGMENTATION; MIXTURE MODEL; NUMERICAL EVALUATIONS; OPTIMIZATION PROCEDURES; PARAMETER VALUES; PORTAL VEINS; REGION GROWING; SEMIAUTOMATIC METHODS; SURGICAL PLANNING; SURGICAL PROCEDURES; TRACKING ALGORITHM; VOXEL INTENSITIES;

COMPUTER SIMULATION; COMPUTERIZED TOMOGRAPHY; IDENTIFICATION (CONTROL SYSTEMS); MEDICAL IMAGING; NUMERICAL METHODS; SURGERY;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; BIOLOGICAL MODEL; BLOOD VESSEL; COMPUTER ASSISTED TOMOGRAPHY; HUMAN; IMAGE PROCESSING; LIVER; METABOLISM; METHODOLOGY; PORTAL VEIN; RADIOGRAPHY; THREE DIMENSIONAL IMAGING; VASCULARIZATION;

ALGORITHMS; BLOOD VESSELS; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; LIVER; MODELS, BIOLOGICAL; PORTAL VEIN; TOMOGRAPHY, X-RAY COMPUTED;

EID: 79954573225     PISSN: 1475925X     EISSN: 1475925X     Source Type: Journal    
DOI: 10.1186/1475-925X-10-30     Document Type: Article

References (31)

1. Masutani Y, Uozumi K, Masaaki A, Kuni O. Liver CT image processing: A short introduction of the technical elements. European Journal of Radiology 2006, 58:246-251. 10.1016/j.ejrad.2005.11.044, 16427756.
2. Lamecker H, Zachow S, Haberl H, Stiller M. Medical Applications for Statistical 3D Shape Models. Book Computer Aided Surgery around the Head 2005, 61. Berlin: VDI, S. Weber, vol. 17. pp. 61.
3. Soler L, Delingette H, Malandain G, Montagnat J, Ayache N, Clement JM, Koehl C, Dourthe O, Mutter D, Marescaux J. Fully automatic anatomical, pathological, and functional segmentation from CT scans for hepatic surgery. Computer Aided Surgery 2001, 6:131-142. 10.3109/10929080109145999, 11747131.
4. Fujimoto H, Gu L, Kaneko T. Recognition of Abdominal Organs Using 3D Mathematical Morphology. System and Computers in Japan 2002, 33:75-83.
5. Kim S, Yoo S, Kim S, Kim J, Park J. Segmentation of kidney without using contrast medium on abdominal CT image. Book 5th International Conference on Signal Processing Proceedings 2000, 2:1147-1152. Beijing, pp. 1147-1152.
6. Osher S, Sethian J. Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations. Journal of Computational Physics 1998, 79:12-49.
7. Gamarendi JF, Malpica N, Martel J, Schiavi E. Automatic Segmentation of the Liver in CT Using Level Sets Without Edges. Pattern Recognition and Image Analysis Lecture Notes in Computer Science 2007, 4477:161-168.
8. Chan TF, Vese LA. Active Countours Without Edges. IEEE Transactions on Image Processing 2001, 10:266-277. 10.1109/83.902291, 18249617.
9. Fernandez-de-Manuel L, Rubio JL, Ledesma-Carbayo MJ, Pascau J, Tellado JM, Ramon E, Desco M, Santos A. 3D liver segmentation in preoperative CT images using a level-sets active surface method. International Conference of the IEEE EMBS 2009, 1:3625-3628. Minessota, pp. 3625-3628.
10. Oliveira DAB, Feitosa RQ, Correia MM. Liver Segmentation using Level Sets and Genetic Algorithms. Fourth International Conference on Computer Vision Theory and Applications 2009, 2:154-159. Porto, pp. 154-159.
11. Oliveira DAB, Feitosa RQ, Correia MM. Automatic Couinaud liver and veins segmentation from CT images. Biosignals - International Conference on Bio-Inspired Systems and Signal Processing 2008, 1:249-252. Funchal, pp. 249-252.
12. Oliveira DAB, Feitosa RQ, Correia MM. Genetic Adaptation of Level Sets Parameters for Medical Imaging Segmentation. Biomedical Image Analysis and Machine Learning Technologies: Applications and Techniques 2010, 1:150-165. New York, Gonzalez FA, Romero E, pp. 150-165.
13. Couinaud C. Le foie: études anatomiques et chirurgicales 1957, Paris: Masson.
14. Sethian J. Level Set Methods and Fast Marching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science 1999, New York: Cambridge University Press.
15. Malladi R, Sethian JA, Vemuri BC. Shape modeling with front propagation: a level set approach. IEEE Transactions on Pattern Analysis and Machine Intelligence 1995, 17:158-175.
16. McInerney T, Terzopoulos D. Deformable Models in Medical Image Analysis: A survey. Medical Image Analysis 1996, 2:91-108.
17. Zhang Y. A survey on evaluation methods for image segmentation. Pattern Recognition 1996, 29:1335-1346.
18. Chabrier S, Emile B, Rosenberger C, Laurent H. Unsupervised performance evaluation of image segmentation. EURASIP Journal on Applied Signal Processing 2006, 2006:1-12. 1474139, 16758000.
19. Kubassuva O, Boesen M, Bliddal H. General Framework for Unsupervised Evaluation of Quality of Segmentation Results. ICIP Proceedings 2008, 3036-3039. San Diego, pp. 3036-3039.
20. Schmiedle F, Drechsler N, Grosse D, Drechsler R. Heuristic learning based on genetic programming. Genetic Programming and Evolvable Machines 2002, 3:363-388.
21. Michalewicz Z. Genetic Algorithms + Data Structures = Evolution Programs 1994, Berlin: Springer-Verlag.
22. Davis L. Handbook of Genetic Algorithms 1990, New York: Van Nostrand Reinhold Company.
23. Costa GAOP, Feitosa RQ, Cazes TB, Feijó B. Genetic Adaptation of Segmentation Parameters. Book Object-Based Image Analysis: Spatial concepts for knowledge-driven remote sensing applications 2008, 679-695. New York: Springer-Verlag, T. Blaschke, S. Lang, G. Hayeds, pp. 679-695.
24. Levenberg K. A Method for the Solution of Certain Non-Linear Problems in Least Squares. The Quarterly of Applied Mathematics 1944, 2:164-168.
25. Marquadt D. An Algorithm for Least-Squares Estimation of Nonlinear Parameters. Journal of Applied Mathematics 1963, 11:431-441.
26. Soille P. Morphological Image Analysis: Principles and Applications 2003, Heildelberg: Springer-Verlag.
27. Heimann T, Ginneken B, Styner M, Arzhaeva Y, Aurich V, Bauer C, Beck A, Becker C, Beichel R, Bekes G, et al. Comparison and Evaluation of Methods for Liver Segmentation from CT datasets. IEEE Transactions on Medical Imaging 2009, 28:1251-1265.
28. Yoo TS, Ackerman MJ, Lorensen WE, Schroeder W, Chalana V, Aylward S, Metaxes D, Whitaker R. Engineering and Algorithm Design for an Image Processing API: A Technical Report on ITK - The Insight Toolkit. Book Medicine Meets Virtual Reality Proceedings 2002, 586-592. Amsterdam: IOS Press, J. Westwood, pp. 586-592.
29. Fasel J, Selle D, Evertsz C, Terrier F, Peitgen H, Gailloud P. Segmental anatomy of the liver: Poor correlation with CT. Radiology 1998, 206:151-156.
30. Fischer L, Thorn M, Neumann J, Schäobinger M, Heimann T, Grenacher L, Meinzer H, Friess H, Bäuchler M. The segments of the hepatic veins: is there a spatial correlation to the Couinaud liver segments?. European Journal of Radiology 2005, 53:245-255. 10.1016/j.ejrad.2004.02.003, 15664288.
31. Machado M. Segmentação hepática de Couinaud: além dos olhos do radiologista. Radiologia Brasileira 2003, 23:3-4.