A Holistic approach for the detection of media-adventitia border in IVUS

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

Volumn 6893 LNCS, Issue PART 3, 2011, Pages 411-419

  Ciompi, Francesco ^a,b   Pujol, Oriol ^a,b   Gatta, Carlo ^a,b   Carrillo, Xavier ^c   Mauri, Josepa ^c   Radeva, Petia ^a,b  

^a UNIVERSITY OF BARCELONA   (Spain)

^b Barcelona Perception Computing Lab   (Spain)

^c HOSPITAL UNIVERSITARI GERMANS TRIAS I PUJOL   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATIC DETECTION; HOLISTIC APPROACH; INTRAVASCULAR ULTRASOUND; MEAN DISTANCES; QUALITY MEASURES; ROBUST COMPUTATION;

HISTOLOGY; TISSUE; ULTRASONIC APPLICATIONS; ULTRASONICS;

MEDICAL COMPUTING;

ALGORITHM; ARTICLE; AUTOMATION; COMPUTER PROGRAM; CONNECTIVE TISSUE; DIAGNOSTIC IMAGING; ENDOSCOPIC ECHOGRAPHY; HUMAN; IMAGE PROCESSING; METHODOLOGY; PATHOLOGY; REPRODUCIBILITY; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING; TUNICA MEDIA; VEIN;

ALGORITHMS; AUTOMATION; CONNECTIVE TISSUE; DIAGNOSTIC IMAGING; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MODELS, STATISTICAL; REPRODUCIBILITY OF RESULTS; SOFTWARE; TUNICA MEDIA; ULTRASONOGRAPHY, INTERVENTIONAL; VEINS;

EID: 82255183292     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-23626-6_51     Document Type: Conference Paper

References (16)

1. Unal, G., Bucher, S., Carlier, S., Slabaugh, G., Fang, T., Tanaka, K.: Shape-driven segmentation of the arterial wall in intravascular ultrasound images. TITB 12(3), 335-347 (2008)
2. Gil, D., Hernandez, A., Rodriguez, O., Mauri, J., Radeva, P.: Statistical strategy for anisotropic adventitia modelling in ivus. TMI 25, 768-778 (2006)
3. Zhu, H., Liang, Y., Friedman, M.H.: Ivus image segmentation based on contrast. In: SPIE, vol. 4684, pp. 1727-1733 (2002)
4. Papadogiorgaki, M., Mezaris, V., Chatzizisis, Y.S., Giannoglou, G.D., Kompatsiaris, I.: Automated ivus contour detection using intensity features and radial basis function approximation. In: CBMS (2007)
5. Sanz-Requena, R., Moratal, D., Garca-Snchez, D.R., Bod, V., Rieta, J.J., Sanchis, J.M.: Automatic segmentation and 3d reconstruction of intravascular ultrasound images for a fast preliminar evaluation of vessel pathologies. CMIG 31(2), 71-80 (2007)
6. Cardinal, M.H.R., Meunier, J., Soulez, G., Maurice, R.L., Therasse, E., Cloutier, G.: Intravascular ultrasound image segmentation: a three-dimensional fast-marching method based on gray level distributions. TMI 25(5), 590-601 (2006)
7. Giannogloua, G.D., Chatzizisisa, Y.S., Koutkiasb, V., Kompatsiarisc, I., Papadogiorgakic, M., Mezarisc, V., Parissic, E., Diamantopoulosd, P., Strintzisc, M.G., Maglaverasb, N., Parcharidisa, G.E., Louridasa, G.E.: A novel active contour model for fully automated segmentation of intravascular ultrasound images: In vivo validation in human coronay arteries. CBM 37, 1292-1302 (2007)
8. Plissiti, M.E., Fotiadis, D.I., Michalis, L.K., Bozios, G.E.: An automated method for lumen and media-adventitia border detection in a sequence of ivus frames. TITB 8(2), 131-141 (2004)
9. Kumar, S., Hebert, M.: Discriminative random fields. IJCV 68(2), 179-201 (2006)
10. Ciompi, F., Pujol, O., Gatta, C., Rodriguez-Leor, O., Mauri-Ferre, J., Radeva, P.: Fusing in-vitro and in-vivo intravascular ultrasound data for plaque characterization. IJCI 26, 763-779 (2010)
11. Ciompi, F., Pujol, O., Fernandez-Nofrerias, E., Mauri, J., Radeva, P.: Ecoc random fields for lumen segmentation in radial artery ivus sequences. In: Yang, G.-Z., Hawkes, D., Rueckert, D., Noble, A., Taylor, C. (eds.) MICCAI 2009. LNCS, vol. 5762, pp. 869-876. Springer, Heidelberg (2009)
12. Sathyaranayana, S., Carlier, S., Wenguang, L., Thomas, L.: Characterization of atherosclerotic plaque by spectral similarity of radiofrequency intravascular ultrasound signals. EuroIntervention 5, 133-139 (2009)
13. Ciompi, F., Pujol, O., Radeva, P.: A meta-learning approach to conditional random fields using error-correcting output codes. In: IEEE International Conference on Pattern Recognition (ICPR), pp. 710-713 (2010)
14. Dietterich, T.G., Bakiri, G.: Solving multiclass learning problems via error-correcting output codes. JAIR 2, 263-286 (1995)
15. Bautista, M.A., Baro, X., Pujol, O., Radeva, P., Vitria, J., Escalera, S.: Compact evolutive design of error-correcting output codes. In: ECML (2010)
16. Yedidia, J.S., Freeman, W.T., Weiss, Y.: Understanding belief propagation and its generalizations. (TR-2001-22), pp. 239-269 (2002)