By Joao Manuel R S Tavares, R.M. Natal Jorge
VipIMAGE 2015 comprises invited lectures and entire papers provided at VIPIMAGE 2015 - V ECCOMAS Thematic convention on Computational imaginative and prescient and scientific photograph Processing (Tenerife, Canary Islands, Spain, 19-21 October, 2015). overseas contributions from 19 international locations offer a entire insurance of the present cutting-edge within the fields of: 3D imaginative and prescient; Computational Bio-Imaging and Visualization; Computational imaginative and prescient; machine Aided prognosis, surgical procedure, remedy and remedy; info Interpolation, Registration, Acquisition and Compression; commercial Inspection; photo Enhancement; photograph Processing and research; picture Segmentation; scientific Imaging; scientific Rehabilitation; Physics of scientific Imaging; form Reconstruction; sign Processing; Simulation and Modelling; software program improvement for photo Processing and research; Telemedicine structures and their Applications;
Tracking and research of circulate and Deformation; digital Reality.
Computational imaginative and prescient and scientific snapshot Processing. VipIMAGE 2015 will be worthwhile to lecturers, researchers and pros in Biomechanics, Biomedical Engineering, Computational imaginative and prescient (image processing and analysis), machine Sciences, Computational Mechanics, sign Processing, drugs and Rehabilitation.
Read Online or Download Computational Vision and Medical Image Processing V: Proceedings of the 5th Eccomas Thematic Conference on Computational Vision and Medical Image ... 2015, Tenerife, Spain, October 19-21, 2015) PDF
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Additional resources for Computational Vision and Medical Image Processing V: Proceedings of the 5th Eccomas Thematic Conference on Computational Vision and Medical Image ... 2015, Tenerife, Spain, October 19-21, 2015)
Intell. 33(7), 1384–1399. X. G. ). Interactive volume segmentation with differential image foresting transforms. IEEE Trans. Med. Imag. 23(9), 1100–1108. , J. A. Lotufo (2004). The image foresting transform: theory, algorithms, and applications. IEEE Trans. Pattern Anal. Mach. Intell. 26(1), 19–29. , G. Wu, Y. Gao, & D. Shen (2014, Oct). Learning to rank atlases for multiple-atlas segmentation. IEEE Trans. Med. Imaging 33(10), 1939–1953. V. X. Falcão (2014, Dec). Hybrid approaches for interactive image segmentation using the Live Markers paradigm.
A few aspects distinguish the works in FOSMs. In (Udupa et al. 2011, Udupa et al. 2012, Udupa et al. 2014), the hierarchy of the objects guides segmentation, and the object search involves limited translation and rotation of the models, according to parameters learned by training. Object recognition is done first and then delineation is applied as a separated step. In contrast, the FOSMs in (Miranda et al. 2008, Miranda et al. 2009, Miranda et al. 2010, Phellan 2014, Phellan et al. 2015) exploit the synergism between model and delineation algorithm for recognition and delineation as a single step in the optimum object search guided by a criterion function.
Tai (2006b). A variant of the level set method and applications to image segmentation. Math. Comp. 75(255), 1155–1174. -c. Tai, S. Leung, & H. Huang (2014). A new continuous max-flow algorithm for multiphase image segmentation using super-level set functions. Journal of Visual Communication and Image Representation 25(6), 1472–1488. Osher, S. & J. Sethian (1988). Fronts propagating with curvature dependent speed: algorithms based on hamilton-jacobi formulations. J. Comput. Phys. 79(1), 12–49. , Y.
Computational Vision and Medical Image Processing V: Proceedings of the 5th Eccomas Thematic Conference on Computational Vision and Medical Image ... 2015, Tenerife, Spain, October 19-21, 2015) by Joao Manuel R S Tavares, R.M. Natal Jorge