Emmanuel Maitre - Homepage
Emmanuel Maitre - Homepage

Level-set, Optimal transport, application to image analysis 2012-2019

Welcome on the web page of this lecture, that I share with Charles Dapogny. You will find here lecture notes and python notebooks.

  • Lectures
  1. Active contour using the level-set method : notes and notebook to download and test.
  2. Primal-dual algorithm and applications : notebook to download and test.
  3. Optimal transport : generic case and lab on obstacle problems.
  • 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).
  3. Adaptive level set evolution starting with a constant function, Yan Wang, Chuanjiang He, Applied Mathematical Modelling (2012)
  4. 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. [Emilien Rougier and Sophia Vilayvong]
  5. 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.
  6. Level set evolution with locally linear classification for image segmentation, WANG, Ying, XIANG, Shiming, PAN, Chunhong, et al. Pattern Recognition, 2012.
  7. 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.
  8. 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.
  9. 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.
  10. ORACM: Online Region-Based Active Contour Model, FATIH TALU, M. Expert Systems with Applications 40 (2013) 6233–6240.
  11. 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.
  12. Active contour model driven by local histogram fitting energy,LIU, Weiping, SHANG, Yanfeng, et YANG, Xin. Pattern Recognition Letters 34 (2013) 655–662.
  13. 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.
  14. 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.[Manon Vialle and Rémi Massiéra]
  15. Vector-Valued Image Processing by Parallel Level Sets., EHRHARDT, M. et ARRIDGE, Simon R. IEEE TRANSACTIONS ON IMAGE PROCESSING, 2013.
  16. 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).
  17. Four-Color Theorem and Level Set Methods for Watershed Segmentation, Erlend Hodneland, Xue-Cheng Tai, Hans-Hermann Gerdes, Int J Comput Vis (2009).
  18. 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). [DARCHE Clément and HAAG Martin / Alexis Bigé]
  19. 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).
  20. 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).
  21. Tensor diffusion level set method for infrared targets contours extraction, Meng Li, Chuanjiang He, Yi Zhan, Infrared Physics & Technology (2012).
  22. 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).
  23. Colour, texture, and motion in levelset based segmentation and tracking, Thomas Broxa, Mikaël Roussonb, Rachid Derichec, Joachim Weickert, Image and Vision Computing (2010). [Alexandre Frances]
  24. A high-throughput active contour scheme for segmentation of histopathological imagery, Jun Xu, Andrew Janowczyk, Sharat Chandran, Anant Madabhushi, Medical Image Analysis (2011).
Articles Level-set / other applications than image
  1. A level-set approach for inverse problems involving obstacles, SANTOSA Fadil, COCV 1996. [Mayra Hernandez and Maxime Fays]
  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)
  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). [Dollomaja Borana, Martin Clara]
  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.
  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. [Nicolas Parent and Laurendeau Matthieu]
  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.
  9. Modeling holes and inclusions by level sets in the extended nite-element method, Natarajan Sukumar, David Chopp, Nicolas Moës, Ted Belytschko, 2001.
  10. Snakes: Active Contour Models, MICHAEL KASS, ANDREW WITKIN, and DEMETRI TERZOPOULOS, 1988.
Articles on seismic imaging and geophysics applications of OT
  1. Analysis of optimal transport and related misfit functions in FWI, Yunan Yang and Björn Engquist, proc. SEG International Exposition and 87th Annual Meeting, 2017.
  2. An optimal transport approach for seismic tomography: Application to 3D full waveform inversion, L. Métivier, R. Brossier, Q. Mérigot, E. Oudet, J. Virieux, submitted, 2016
  3. OPTIMAL TRANSPORT FOR SEISMIC FULL WAVEFORM INVERSION, Björn Engquist, Brittany Froese, Yunan Yang, 2016
  4. APPLICATION OF THE WASSERSTEIN METRIC TO SEISMIC SIGNALS,Björn Engquist, Brittany Froese, 2013. [Mathurin Charles / Chris Janaqi and Nathan Shourick]
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.
  2. Texture Mapping via Optimal Mass Transport, Ayelet Dominitz, Allen Tannenbaum, IEEE Trans Vis Comput Graph. (2010)
  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).
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lsto.txt · Last modified: 2020/01/21 21:35 by maitre