Professor of Rouen University, France
Su Ruan received her MS and PhD degrees in Image Processing from Rennes University, France, in 1989 and 1993 respectively. She was previously an associate professor at Caen University from 1993 to 2003 and a full professor at Reims University from 2003 to 2010. She is presently a full professor at Rouen University, France.
Her main area of research is image processing, particularly in the fields of image segmentation, pattern recognition, and data fusion. Her developments include advanced machine learning techniques, shape models, non rigid registration, graph-based image segmentation and data fusion strategies, applicable to medical imaging, such as MRI, PET-CT. She has supervised 10 PhD theses and is currently supervising 3 ones. Her work has appeared in prestigious journals and has been presented at many international conferences.
Yu Guo, Su Ruan, “Signal Separation with A Priori Knowledge Using Sparse Representation”, In Amitava Chatterjee, Hadi Nobahari,and Patrick Siarry, editors, Advances in Heuristic Signal Processing and Applications, pp 315-332, Springer, 2013.
Benoit Lelandais, Isabelle Gardin, Laurent Mouchard, Pierre Vera, Su Ruan, “Dealing with uncertainty and imprecision in image segmentation using belief function theory”, Elsevier, International Journal of Approximate Reasoning, Volume 55, Issue 1, Part 3, Pages 376-387, 2014.
Ines Ketata, Lamia Sallemi, Frédéric Morain-Nicolier Mohamed Ben Slima, Alexandre Cochet, Khalil Chtourou, Su Ruan & Ahmed Ben Hamida, ”Factor Analysis-based Approach for Early Uptake Automatic Quantification of Breast Cancer by 18F-FDG PET Image Sequence”, Elsevier, Biomedical Signal Processing and Control, Vol.9. pp.19–31, 2014.
Damien Grosgeorge, Caroline Petitjean, Bernard Dubray, and Su Ruan, " Esophagus Segmentation from 3D CT Data Using Skeleton Prior-Based Graph Cut", Computational and Mathematical Methods in Medicine, Volume 2013, Article ID 547897, 6 pages, 2013.
N. D. Grosgeorge, C. Petitjean, J.-N. Dacher, S. Ruan, "Graph cut
segmentation with a statistical shape model in cardiac MRI", Elsevier,
Computer Vision and Image Understanding, Vol.117, pp.1027-1035,
XiangBo Lin, Su Ruan, Tian Shuang Qiu and DongMei Guo, "Non-rigid Medical Image Registration Based on Mesh Deformation Constraints," Computational and Mathematical Methods in Medicine, Volume 2013 (2013), Article ID 373082, 8 pages, 2013.
N. Zhang, S.Ruan, S. Lebonvallet, Q. Liao, Y. Zhu, "Kernel feature selection to fuse multi-spectral MRI images for brain tumor segmentation", Elsevier, Computer Vision and Image Understanding, Vol.115(2), pp.256-269, 2011.
Y. Guo, S. Ruan, J. Landré et P. Walker, "A Priori Knowledge Based Frequency-domain Quantification of Prostate Magnetic Resonance Spectroscopy", Elsevier, Biomedical Signal Processing and Control,Vol.6(1), pp.13-20, 2011.
Z. Chen, T.Qiu and S. Ruan, "A Segmentation Algorithm for Brain MR Images Using Fuzzy Model and Level Sets", International Journal of Innovative Computing Information and Control, Vol.6 (12), pp. 5565-5574, 2010.
Y. Guo, S. Ruan, J. Landré, J-M. Constans, "A Sparse Representation Method for Magnetic Resonance Spectroscopy Quantification", IEEE Transactions on Biomedical Engineering, 57(7): 1620-1627, 2010.
X. Lin, T. Qiu, F. Morain-Nicolier, S. Ruan, "A Topology Preserving Non-Rigid Registration Algorithm with lntegration Shape Knowledge to Segment Brain Subcortical Structures from MRI Images", Elsevier, Pattern Recognition, 43(7):2418-2427, 2010.
E. Baudrier, F. Nicolier, G. Millon, S. Ruan, "Binary-image comparison with local-dissimilarity quantification", Elsevier, Pattern Recognition, Vol.41 (5), pp. 1461 -1478, 2008.
E. Baudrier, G. Million, F. Nicolier, S. Ruan, "Hausdorff distance based multiresolution maps applied to an image classification", Maney Publishing, lmaging Science Journal, Vol. 55 (3), pp. 164- 174, 2007.
W. Dou, S. Ruan, D. Bloyet, J-M. Constans "A framework of fuzzy information fusion for the segmentation of brain tumor tissues on MR images", Elsevier, lmage and Vision Computing, Vo1.25 (2)) pp. 164-171, 2007.
W. Dou, Y. Ren, Q. Wu, S. Ruan, Y. Chen, D. Bloyet, J-M. Constans, "Fuzzy kappa for the agreement measure of fuzzy classifications", Elsevier, Neurocomputing, Vol.70, pp. 726-734, 2007.
Yu Guo, Su Ruan, Paul Walker, Yuanming Feng, "Prostate Cancer Segmentation from Multiparametric MRI Based on Fuzzy Bayesian Model ", IEEE-ISBI, Beijing, April 2014.
D. Grosgeorge, C. Petitjean, S. Ruan, "Joint Segmentation of Right and Left Cardiac Ventricles Using Multi-Label Graph Cut", IEEE-ISBI, Beijing, April 2014.
Hongmei Mi, Caroline Petitjean, Pierre Vera, Bernard Dubray, Su Ruan, "Automatic Lung Tumor Segmentation on PET Images Based on Random Walks and Tumor Growth Model", IEEE-ISBI, Beijing, April 2014.
Hongmei Mi, Caroline Petitjean, Su Ruan, Pierre Vera, Bernard Dubray, "Predicting lung tumor evolution during radiotherapy from PET images using a patient specific model", IEEE-ISBI, San Francisco, April 2013.
Benoît Lelandais, Isabelle Gardin,, Laurent Mouchard, Pierre Vera and Su Ruan, "Segmentation of Biological Target Volumes on Multi-tracer PET Images Based on Information Fusion for Achieving Dose Painting in Radiotherapy", MICCAI’2012, pp.545-549, Nice, France, Sept. 2012.
Y. Guo, S. Ruan, J. Landré, Y. Zhang1, X. Ming1 and Y. Feng, “Localization of prostate cancer based on fuzzy fusion of multispectral MRI”, World Congress on Medical Physics and Biomedical Engineering, pp. 1844-1846, Beijing, May 2012.
Onoma D. P., Ruan S., Isabelle G., Monnehan G. A., Modzelewski R., Vera P., "3D random walk based segmentation for lung tumor delineation in pet imaging", IEEE-ISBI, Barcelona, May 2012.
Lelandais B., Gardin I., Mouchard L., Vera P., Ruan S., "Using belief function theory to deal with uncertainties and imprecisions in image processing", The 2nd International Conference on Belief Functions, Compiegne, May, 2012.
S. Ruan, N. Zhang, Q. Liao and Y. Zhu, "Image fusion for following-up brain tumor evolution", IEEE-ISBI, Chicago, USA, April 2011.