Download Computational Vision and Medical Image Processing V: by Joao Manuel R S Tavares, R.M. Natal Jorge PDF

By Joao Manuel R S Tavares, R.M. Natal Jorge

VipIMAGE 2015 includes invited lectures and whole papers provided at VIPIMAGE 2015 - V ECCOMAS Thematic convention on Computational imaginative and prescient and clinical snapshot Processing (Tenerife, Canary Islands, Spain, 19-21 October, 2015). overseas contributions from 19 international locations supply a finished assurance of the present cutting-edge within the fields of: 3D imaginative and prescient; Computational Bio-Imaging and Visualization; Computational imaginative and prescient; desktop Aided prognosis, surgical procedure, treatment and therapy; info Interpolation, Registration, Acquisition and Compression; commercial Inspection; snapshot Enhancement; picture Processing and research; photograph Segmentation; clinical Imaging; scientific Rehabilitation; Physics of scientific Imaging; form Reconstruction; sign Processing; Simulation and Modelling; software program improvement for picture Processing and research; Telemedicine structures and their Applications;
Tracking and research of stream and Deformation; digital Reality.

Computational imaginative and prescient and clinical snapshot Processing. VipIMAGE 2015
will be worthy to teachers, researchers and execs in Biomechanics, Biomedical Engineering, Computational imaginative and prescient (image processing and analysis), desktop Sciences, Computational Mechanics, sign Processing, drugs and Rehabilitation.

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Extra info 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)

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M. -C. Tai (2005). A piecewise constant level set framework. Int. Numer. Anal. Model 2(4), 422–438. , M. -C. Tai (2006a). A binary level set model and some applications to mumford-shah image segmentation. Image Processing, IEEE Transactions on 15(5), 1171–1181. , M. -C. 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.

Pittsburgh, USA. X. K. Udupa (2015). Medical image segmentation using object atlas versus object cloud models. In SPIE, Volume 9415, Orlando, USA, pp. 94151M–94151M–11. Pluim, J. P. , J. Maintz, & M. Viergever (2003, Aug). Mutualinformation-based registration of medical images: a survey. IEEE Trans. Med. Imaging 22(8), 986–1004. K. A. Torigian (2014). Multiple fuzzy object modeling improves sensitivity in automatic anatomy recognition. In SPIE, Volume 9034, San Diego, USA, pp. 90342U–90342U–7. , V.

C. M. M. Genega, E. E. Lenkinski, & A. Madabhushi (2013). Statistical 3D Prostate Imaging Atlas Construction via Anatomically Constrained Registration. In SPIE, Volume 8669, Lake Buena Vista, USA, pp. 1–15. indb 15 9/8/2015 7:41:01 PM This page intentionally left blank Computational Vision and Medical Image Processing V – João Tavares & Natal Jorge (Eds) © 2016 Taylor & Francis Group, London, ISBN 978-1-138-02926-2 Primal-dual method for continuous max-flow approaches Ke Wei Department of Mathematics, Hong Kong University of Science and Technology, Hong Kong Xue-Cheng Tai Department of Mathematics, University of Bergen, Bergen, Norway Tony F.

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