A novel method for registration of US/MR of the liver based on the analysis of US dynamics

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

Volumn 5761 LNCS, Issue PART 1, 2009, Pages 771-778

  Milko, Sergiy ^a   Melvær, Eivind Lyche ^b   Samset, Eigil ^c   Kadir, Timor ^d  

^a IXICO PLC   (United Kingdom)

^b UNIVERSITY OF OSLO   (Norway)

^c Kongsberg SIM   (Norway)

^d SIEMENS AG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

CLINICAL APPLICATION; DATA SETS; HIGH ROBUSTNESS; INTRA-OPERATIVE; LIVER CANCERS; MINIMALLY INVASIVE; MR IMAGES; MULTI-RESOLUTIONS; NOVEL METHODS; OPEN SURGERY; PRE-OPERATIVE PLANNING; PROBABILITY IMAGE; PROBABILITY MAPS; RADIO-FREQUENCY ABLATION; REASONABLE ACCURACY;

COMPUTERIZED TOMOGRAPHY; LIVER; MEDICAL COMPUTING; PROBABILITY;

THREE DIMENSIONAL;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; ECHOGRAPHY; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; LIVER; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; LIVER; MAGNETIC RESONANCE IMAGING; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE; ULTRASONOGRAPHY;

EID: 79551684118     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04268-3_95     Document Type: Conference Paper

References (11)

1. Wein, W., Röper, B., Navab, N.: Integrating Diagnostic B-mode Ultrasonography into CT-based Radiation Treatment Planning. IEEE Trans. on Med. Imag. 26(6), 866-879 (2007)
2. Roche, A., Pennec, X., Malandain, G., Ayache, N.: Rigid Registration of 3D Ultrasound with MR Images: a New Approach Combining Intensity and Gradient Information. IEEE Trans. on Med. Imag. 20(10), 1038-1049 (2001)
3. Mellor, M., Brady, M.: Fluid Registration of Ultrasound Using Multi-scale Phase Estimates. In: Proc. of BMVA 2005 (2005)
4. Maes, F., Collignon, A., Vandermeulen, D., Marchal, G., Suetens, P.: Multimodality Image Registration by Maximization of Mutual Information. IEEE Trans. on Med. Imag. 16(2), 187-198 (1997)
5. Viola, P., Wells, W.M.: Alignment by Maximization of Mutual Information. Int. Journal of Comp. Vision. 24(2), 137-154 (1997) (Pubitemid 127506551)
6. Blackall, J.M., Penney, G.P., King, A.P., Hawkes, D.J.: Alignment of Sparse Free-hand 3-D Ultrasound with Preoperative Images of the Liver Using Models of Respiratory Motion and Deformation. IEEE Trans. on Med. Imag. 24(11), 1405-1416 (2005)
7. Milko, S., Samset, E., Kadir, T.: Segmentation of the Liver in Ultrasound: a Dynamic Texture Approach. Int. Journal of Comp. Assist. Radiol. and Surgery 3(1-2), 143-150 (2008)
8. Milko, S., Samset, R., Kadir, T.: A Novel Dynamic Texture Based Approach for Segmentation and Registration of Liver Ultrasound. In: Proc. of IGSTI 2008 (2008)
9. Doretto, G., Chiuso, A., Wu, Y.N., Soatto, S.: Dynamic Textures. Int. Journal of Comp. Vision 51(2), 91-109 (2003)
10. Boukerroui, D.: Velocity Estimation in Ultrasound Images: A Block Matching Approach. In: Taylor, C.J., Noble, J.A. (eds.) IPMI 2003. LNCS, vol. 2732, pp. 586-598. Springer, Heidelberg (2003)
11. Schneider, T., Neumaier, A.: Algorithm. ARfit - A Matlab Package for the Estimation of Parameters and Eigenmodes of Multivariate Autoregressive Models. ACM Trans. on Math. Software 27, 58-65 (2001)