Emmanuel Maitre - Homepage
Emmanuel Maitre - Homepage

Level-set, Optimal transport, application to image analysis 2012-2017

Welcome on the web page of this lecture, which has been in English since 2014.

  • Lecture notes : version, build on a weekly basis or so …

  • Old french version of lecture notes :

version sep. 2013, with some missing parts …

  • List of articles available for review and oral presentation.

You are supposed to choose one of those, email me your choice (on a first arrived / first served basis). Alternatively, you could find an article (e.g. on google scholar) in link with the lecture, and of course email me about that. Then you will have to prepare 5 slides summing up the article, that you will present for 5 minutes.

Article on Level-set method / contouring methods
  1. Image segmentation using a multilayer level-set approach, Ginmo Chung et Luminita A. Vese, Comput Visual Sci (2009).
  2. Active contours without level sets, R Yildizoglu, JF Aujol, N Papadakis - Proc. ICIP'12 (2012). [Chosen by Déborah Leder]
  3. Mumford–Shah based registration: a comparison of a level set and a phase field approach, M. Droske, W. Ring, M. Rumpf, Comput Visual Sci (2009) [Chosen by Noémie Tasca]
  4. Adaptive level set evolution starting with a constant function, Yan Wang, Chuanjiang He, Applied Mathematical Modelling (2012) [Chosen by Gaétan Bahl]
  5. A Level-Set Method Based on Global and Local Regions for Image Segmentation, ZHAO, Yu Qian, WANG, Xiao Fang, SHIH, Frank Y., et al. International Journal of Pattern Recognition and Artificial Intelligence, 2012, vol. 26, no 01. [Chosen by Tina Nikoukhah]
  6. Robust segmentation of overlapping cells in histopathology specimens using parallel seed detection and repulsive level set, QI, Xin, XING, Fuyong, FORAN, David J., et al. Biomedical Engineering, IEEE Transactions on, 2012, vol. 59, no 3, p. 754-765. [Chosen by Guillaume Betmont]
  7. Level set evolution with locally linear classification for image segmentation, WANG, Ying, XIANG, Shiming, PAN, Chunhong, et al. Pattern Recognition, 2012. [Chosen by Abdelali Darouy]
  8. Detection of the whole myocardium in 2D-echocardiography for multiple orientations using a geometrically constrained level-set, DIETENBECK, Thomas, ALESSANDRINI, Martino, BARBOSA, Daniel, et al. Medical Image Analysis, 2012, vol. 16, no 2, p. 386-401.
  9. Multi-object spring level sets (MUSCLE), LUCAS, Blake C., KAZHDAN, Michael, et TAYLOR, Russell H. In : Medical Image Computing and Computer-Assisted Intervention–MICCAI 2012. Springer Berlin Heidelberg, 2012. p. 495-503.
  10. Active contours for multi-region image segmentation with a single level set function, DUBROVINA, Anastasia, ROSMAN, Guy, et KIMMEL, Ron. In : Scale Space and Variational Methods in Computer Vision. Springer Berlin Heidelberg, 2013. p. 416-427. [Chosen by Rafik Siala]
  11. ORACM: Online Region-Based Active Contour Model, FATIH TALU, M. Expert Systems with Applications 40 (2013) 6233–6240. [Chosen by Mikaël MULLER]
  12. Image Gradient Based Level Set Methods in 2D and 3D, XIE, Xianghua, YEO, Si Yong, MIRMEHDI, Majid, et al. In : Deformation Models. Springer Netherlands, 2013. p. 101-120.
  13. Active contour model driven by local histogram fitting energy,LIU, Weiping, SHANG, Yanfeng, et YANG, Xin. Pattern Recognition Letters 34 (2013) 655–662. [Chosen by Hugo Fournier]
  14. A multiple object geometric deformable model for image segmentation, John A. Bogovic, Jerry L. Prince, Pierre-Louis Bazin, Computer Vision and Image Understanding, Volume 117, Issue 2, February 2013, Pages 145-157.
  15. A local region-based Chan–Vese model for image segmentation, LIU, Shigang et PENG, Yali. Pattern Recognition, 2012, vol. 45, no 7, p. 2769-2779.
  16. Vector-Valued Image Processing by Parallel Level Sets., EHRHARDT, M. et ARRIDGE, Simon R. IEEE TRANSACTIONS ON IMAGE PROCESSING, 2013.
  17. Graph Cut Optimization for the Piecewise Constant Level Set Method Applied to Multiphase Image Segmentation, Egil Bae and Xue-Cheng Tai, Lecture Notes in Computer Science (2009).
  18. A Review of Statistical Approaches to Level Set Segmentation: Integrating Color, Texture, Motion and Shape, D. Cremers et al, International Journal of Computer Vision (2007).[Chosen by Hugo Mathias]
  19. Four-Color Theorem and Level Set Methods for Watershed Segmentation, Erlend Hodneland, Xue-Cheng Tai, Hans-Hermann Gerdes, Int J Comput Vis (2009). [chosen by Quentin Legros]
  20. Active contours with selective local or global segmentation: A new formulation and level set method, Kaihua Zhang, Lei Zhang, Huihui Song, Wengang Zhou, Image and Vision Computing (2010). [Chosen by Sophie Théry]
  21. Segmentation of interest region in medical volume images using geometric deformable model, Myungeun Lee, Wanhyun Cho, Sunworl Kim, Soonyoung Park, Jong Hyo Kim, Computers in Biology and Medicine (2012).
  22. Fast and Robust Clinical Triple-Region Image Segmentation Using One Level Set Function, Shuo Li1, Thomas Fevens, Adam Krzyzak, Chao Jin, and Song Li, Lecture Notes in Computer Science (2006).
  23. Tensor diffusion level set method for infrared targets contours extraction, Meng Li, Chuanjiang He, Yi Zhan, Infrared Physics & Technology (2012).
  24. A Binary Level Set Model and some Applications to Mumford-Shah Image Segmentation, Johan Lie, Marius Lysaker and Xue-Cheng Tai, IEEE Transactions on Image Processing (2006).
  25. Colour, texture, and motion in levelset based segmentation and tracking, Thomas Broxa, Mikaël Roussonb, Rachid Derichec, Joachim Weickert, Image and Vision Computing (2010).[Chosen by Gautier Marçon]
  26. A high-throughput active contour scheme for segmentation of histopathological imagery, Jun Xu, Andrew Janowczyk, Sharat Chandran, Anant Madabhushi, Medical Image Analysis (2011).
  27. An overview of the Mumford-Shah problem, Milan J. Math (2003). [Chosen by Thomas Coupechoux]
Articles Level-set / other applications than image
  1. A level-set approach for inverse problems involving obstacles, SANTOSA Fadil, COCV 1996. [Chosen by Valentin Blais]
  2. A Simple Level Set Method for Solving Stefan Problems, S. Chen, B. Merriman, S. Osher, and P. Smereka, Journal of Computational Physics, 135, 8–29 (1997) [Chosen by Sébastien Riffaud]
  3. Fast Surface Reconstruction Using the Level Set Method, Hong-Kai Zhao, Stanley Osher, Ronald Fedkiw, In Variational and Level Set Methods in Computer Vision, 2001. Proceedings. IEEE Workshop on (pp. 194-201). [Chosen by Ivan Dagès]
  4. Structural optimization using sensitivity analysis and a level-set method, Gr egoire Allaire, François Jouve et Anca-Maria Toader, Journal of Computational Physics 194 (2004) 363–393
  5. A new hole insertion method for level set based structural topology optimization, DUNNING, Peter D. et ALICIA KIM, H. International Journal for Numerical Methods in Engineering, 2013, vol. 93, no 1, p. 118-134. [Chosen by Vincent Heurtin]
  6. A topology optimization method based on the level set method incorporating a fictitious interface energy, YAMADA, Takayuki, IZUI, Kazuhiro, NISHIWAKI, Shinji, et al. Computer Methods in Applied Mechanics and Engineering, 2010, vol. 199, no 45, p. 2876-2891. [Chosen by Thibaud Véron]
  7. A new method for the level set equation using a hierarchical-gradient truncation and remapping technique, KOHNO, Haruhiko et NAVE, Jean-Christophe. Computer Physics Communications 184 (2013) 1547–1554.
  8. A Real-Time Algorithm for the Approximation of Level-Set-Based Curve Evolution, IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 17, NO. 5, MAY 2008. [Chosen by Mathias Biehler]
Articles on optimal transport
  1. Regularized discrete optimal transport, Ferradans, S., Papadakis, N., Rabin, J., Peyré, G., & Aujol, J. F., in Scale Space and Variational Methods in Computer Vision Volume 7893 of the series Lecture Notes in Computer Science pp 428-439. Springer Berlin Heidelberg. 2013. [Chosen by Quentin Lisack]
  2. Texture Mapping via Optimal Mass Transport, Ayelet Dominitz, Allen Tannenbaum, IEEE Trans Vis Comput Graph. (2010) [Chosen by Charlotte Girardot]
  3. An efficient numerical algorithm for the L2 optimal transport problem with periodic densities, SAUMIER, Louis-Philippe, AGUEH, Martial, et KHOUIDER, Boualem. IMA Journal of Applied Mathematics, 2013, p. 1-23.
  4. From Knothe's rearrangement to Brenier's optimal transport map, BONNOTTE, Nicolas. SIAM Journal on Mathematical Analysis, 2013, vol. 45, no 1, p. 64-87.
  5. Wasserstein active contours, PEYRÉ, Gabriel, FADILI, Jalal, et RABIN, Julien. In : Image Processing (ICIP), 2012 19th IEEE International Conference on. IEEE, 2012. p. 2541-2544.
  6. Variational Earth Mover's Distance for Image Segmentation, LI, Peihua et WANG, Qilong. In : Image and Graphics (ICIG), 2013 Seventh International Conference on. IEEE, 2013. p. 236-242.
  7. An Efficient Numerical Method for the Solution of the L_2 Optimal Mass Transfer Problem, Eldad Haber, Tauseef Rehman, and Allen Tannenbaum, SIAM J Sci Comput. (2010) .
  8. Image Sequence Interpolation Based on Optical Flow, Segmentation, and Optimal Control, Kanglin Chen and Dirk A. Lorenz, IEEE Transactions on Image Processing (2012).
  9. Geodesic Shape Retrieval via Optimal Mass Transport, Julien Rabin, Gabriel Peyré, and Laurent D. Cohen, 11th European Conference on Computer Vision, Heraklion, Crete : Greece (2010).[Chosen by Coline Seppecher and Thomas Cormot]
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lsto.txt · Last modified: 2017/02/09 13:57 by maitre