Hacheme AYASSO

Hacheme AYASSO

Hacheme AYASSO

Enseignant-Chercheur Titulaire

Personnel UGA Permanent
Bayesian inference for inverse problems applied for medical and physical signals.

Site Ampère

Bureau : B303

Téléphone : 04 76 82 71 04

Biographie

(à compléter)

Publications / Travaux


56 documents

Articles dans une revue14 documents

  • Florian Cotte, Michel Desvignes, Hacheme Ayasso, Jean-Michel Vignolle. A sparse dictionary representation approach for anti-scattering grid artifact removal in X-ray images. Biomedical Signal Processing and Control, 2023, 86, pp.105247. ⟨10.1016/j.bspc.2023.105247⟩. ⟨hal-04224501⟩
  • Imane Lemammer, Olivier J.J. Michel, Hacheme Ayasso, Steeve Zozor, Guillaume Bernard. Online mobile C-arm calibration using inertial sensors: a preliminary study in order to achieve CBCT. International Journal of Computer Assisted Radiology and Surgery, 2020, 15, pp.213-224. ⟨10.1007/s11548-019-02061-6⟩. ⟨hal-02357073⟩
  • Mathieu Barthélemy, Vladimir Kalegaev, Anne Vialatte, Etienne Le Coarer, Erik Kerstel, et al.. AMICal Sat and ATISE: two space missions for auroral monitoring. Journal of Space Weather and Space Climate, 2018, 8, A44 (12p.). ⟨10.1051/swsc/2018035⟩. ⟨insu-01900254⟩
  • A. Boucaud, H. Dole, A. Abergel, Hacheme Ayasso, F. Orieux. PSF homogenization for multi-band photometry from space on extended objects. EAS Publications Series, 2016, 78-79, pp.275-285. ⟨10.1051/eas/1678013⟩. ⟨hal-01982482⟩
  • Céline Meillier, Florent Chatelain, Olivier J.J. Michel, Roland Bacon, Laure Piqueras, et al.. SELFI: an object-based, Bayesian method for faint emission line source detection in MUSE deep field data cubes. Astronomy & Astrophysics – A&A, 2016, 588, pp.A140. ⟨10.1051/0004-6361/201527724⟩. ⟨hal-01322356⟩
  • Céline Meillier, Florent Chatelain, Olivier J.J. Michel, Hacheme Ayasso. Nonparametric Bayesian extraction of object configurations in massive data. IEEE Transactions on Signal Processing, 2015, 63 (8), pp.1911-1924. ⟨10.1109/TSP.2015.2403268⟩. ⟨hal-01129038⟩
  • Leila Gharsalli, Hacheme Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. Inverse scattering in a Bayesian framework: application to microwave imaging for breast cancer detection. Inverse Problems, 2014, 30 (11), pp.114011. ⟨10.1088/0266-5611/30/11/114011⟩. ⟨hal-01103456⟩
  • Leila Gharsalli, Hacheme Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. Variational Bayesian inversion for microwave breast imaging. Computer Assisted Methods in Engineering and Science, 2014, 21 (3/4), pp.199-210. ⟨10.24423/cames.38⟩. ⟨hal-01211734⟩
  • H Ayasso, Thomas Rodet, Alain Abergel. A variational Bayesian approach for unsupervised super-resolution using mixture models of point and smooth sources applied to astrophysical map-making. Inverse Problems, 2012, 28 (12), pp.125005.1-125005.31. ⟨10.1088/0266-5611/28/12/125005⟩. ⟨hal-00819220⟩
  • François Orieux, Jean-François Giovannelli, Thomas Rodet, Alain Abergel, H Ayasso, et al.. Super-resolution in map-making based on a physical instrument model and regularized inversion. Application to SPIRE/Herschel.. Astronomy & Astrophysics – A&A, 2012, pp.38. ⟨10.1051/0004-6361/201116817⟩. ⟨hal-00674514⟩
  • H Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. Optical diffraction tomography within a variational Bayesian framework. Inverse Problems in Science and Engineering, 2012, 20 (1), pp.59-73. ⟨10.1080/17415977.2011.624620⟩. ⟨hal-00638296⟩
  • Heddy Arab, Alain Abergel, Emilie Habart, Jeronimo Bernard-Salas, H Ayasso, et al.. Evolution of dust in the Orion Bar with Herschel: I. Radiative transfer modelling. Astronomy and Astrophysics Review, 2012, 541 (A19), pp.10. ⟨10.1051/0004-6361/201118537⟩. ⟨hal-00956204⟩
  • H Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. Bayesian Inversion for Optical Diffraction Tomography. Journal of Modern Optics, 2010, 57 (9), pp.765 – 776. ⟨10.1080/09500340903564702⟩. ⟨hal-00444424⟩
  • H Ayasso, Ali Mohammad-Djafari. Joint NDT Image Restoration and Segmentation Using Gauss-Markov-Potts Prior Models and Variational Bayesian Computation. IEEE Transactions on Image Processing, 2010, 19 (9), pp.2265 – 2277. ⟨10.1109/TIP.2010.2047902⟩. ⟨hal-00494945⟩

Communications dans un congrès35 documents

  • Matthieu Chancel, Hacheme Ayasso, Michel Desvignes, Jean-Michel Vignolle, Eric Lespessailles. Improving Sparse Dictionary Learning with Rejection of Fully Exposed Patches. EUSIPCO 2024 – 32nd European Signal Processing Conference, Aug 2024, Lyon, France. ⟨hal-04850833⟩
  • Hacheme Ayasso, Florian Cotte, Matthieu Chancel, Jean-Michel Vignolle, Michel Desvignes. Une approche bayésienne pour la suppression des grilles anti-diffusion. GRETSI 2023 – XXIXème Colloque Francophone de Traitement du Signal et des Images, GRETSI – Groupe de Recherche en Traitement du Signal et des Images, Aug 2023, Grenobe, France. ⟨hal-04224586⟩
  • Imane Lemammer, Olivier J.J. Michel, Hacheme Ayasso, Steeve Zozor, Guillaume Bernard. Vers de la tomographie volumiqueà faisceau conique sur arceau chirurgical mobile. GRETSI 2019 – XXVIIème Colloque Francophone de Traitement du Signal et des Images, Aug 2019, Lille, France. ⟨hal-02357274⟩
  • Florian Cotte, Michel Desvignes, Hacheme Ayasso, Michel Vignolle. A Bayesian Approach for Anti-Scatter Grid Extraction in x-ray Imaging. ICIP 2018 – 25th IEEE International Conference on Image Processing, Oct 2018, Athènes, Greece. ⟨10.1109/ICIP.2018.8451541⟩. ⟨hal-01982466⟩
  • Leila Gharsalli, Hacheme Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. Nonlinear microwave imaging for breast-cancer using a variational Bayesian algorithm. SIAM Conference on the Life Sciences, Jul 2016, Boston, MA, United States. pp.PP1. ⟨hal-01459711⟩
  • Céline Meillier, Florent Chatelain, Olivier J.J. Michel, Hacheme Ayasso. Contrôle des erreurs pour la détection d’événements rares et faibles dans des champs de données massifs. GRETSI 2015 – XXVème Colloque francophone de traitement du signal et des images, Sep 2015, Lyon, France. ⟨hal-01198721⟩
  • Céline Meillier, Florent Chatelain, Olivier J.J. Michel, Hacheme Ayasso. Error control for the detection of rare and weak signatures in massive data. EUSIPCO 2015 – 23th European Signal Processing Conference, Aug 2015, Nice, France. ⟨hal-01198717⟩
  • Leila Gharsalli, Hacheme Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. A Gauss-Markov mixture prior model for a variational Bayesian approach to microwave breast imaging. CAMA 2014 – IEEE Conference on Antenna Measurements and Applications, Nov 2014, Juan-Les-Pins, France. pp.ID SP13.4. ⟨hal-01103674⟩
  • Leila Gharsalli, Bernard Duchêne, Ali Mohammad-Djafari, Hacheme Ayasso. A gradient-like variational Bayesian approach: Application to microwave imaging for breast tumor detection. ICIP 2014 – 21st IEEE International Conference on Image Processing, Oct 2014, Paris, France. pp.1708-1712, ⟨10.1109/ICIP.2014.7025342⟩. ⟨hal-01266174⟩
  • Leila Gharsalli, Hacheme Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. Variational Bayesian Approach with a heavy-tailed prior distribution for solving a non-linear inverse scattering problem. MaxEnt – 34th International Workshop on Bayesian Inference and Maximun Entropy Methods in Science and Engineering (MaxEnt’14), Sep 2014, Amboise, France. ⟨hal-01103647⟩
  • Florian Aulanier, Hacheme Ayasso, Barbara Nicolas, Philippe Roux, Jerome I. Mars. Sound-speed tomography using angle sensitivity-kernels in an ultrasonic waveguide. UA 2014 – 2nd international conference and exhibition on Underwater Acoustics, Jun 2014, Rhodes, Greece. ⟨hal-01060140⟩
  • Slimane Arhab, Hacheme Ayasso, Bernard Duchêne, Mohammad-Djafari Ali. Optical imaging in a variational Bayesian framework. NCMIP 2014 – 4th International Workshop on New Computational Methods for Inverse Problems (NCMIP2014), May 2014, Cachan, France. pp.012008, ⟨10.1088/1742-6596/542/1/012008⟩. ⟨hal-04806041⟩
  • Leila Gharsalli, Hacheme Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. Variational Bayesian inversion for microwave imaging applied to breast cancer detection. ICIPE 2014 – 8th International Conference on Inverse Problems in Engineering (ICIPE 2014), May 2014, Cracovie, Poland. pp.ID 5-2. ⟨hal-01103636⟩
  • Céline Meillier, Florent Chatelain, Olivier J.J. Michel, Hacheme Ayasso. Non-parametric Bayesian framework for detection of object configurations with large intensity dynamics in highly noisy hyperspectral data. ICASSP 2014 – IEEE International Conference on Acoustics, Speech and Signal Processing, May 2014, Florence, Italy. pp.1905-1909. ⟨hal-00991388⟩
  • Leila Gharsalli, Hacheme Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. Microwave tomography for breast cancer detection within a Variational Bayesian Approach. EUSIPCO 2013 – 21th European Signal Processing Conference, Sep 2013, Marrakech, Morocco. pp.ID1569743387. ⟨hal-00854799⟩
  • Leila Gharsalli, Hacheme Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. Approche bayésienne variationnelle en tomographie micro-onde appliquée à la détection du cancer du sein. GRETSI 2013 – XXIVème Colloque francophone de traitement du signal et des images, Sep 2013, Brest, France. ID411, 4 p. ⟨hal-00854796⟩
  • Leila Gharsalli, Hacheme Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. Microwave imaging within a variational Bayesian framework: application to breast tumor detection. ISSSMA 2013 – Interdisciplinary Symposium on Signals and Systems for Medical Applications (ISSSMA 2013), Jun 2013, Paris, France. ⟨hal-00832372⟩
  • Hacheme Ayasso, Thomas Rodet, Alain Abergel, Karin Dassas. A gradient-like variational Bayesian approach for joint image super-resolution and source separation, application to astrophysical map-making. ICASSP 2013 – 38th IEEE International Conference on Acoustics, Speech and Signal Processing, May 2013, Vancouver, Canada. pp.5830-5834, ⟨10.1109/icassp.2013.6638782⟩. ⟨hal-00832883⟩
  • Hacheme Ayasso. SUPREME: a high-resolution mapmaker. Herschel PACS and SPIRE Map-Making Workshop, Jan 2013, Madrid, Spain. ⟨hal-00985267⟩
  • H Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. A variational Bayesian approach for frequency diverse non-linear microwave imaging. ICIP 2012, Sep 2012, Orlando, United States. pp.2069-2073. ⟨hal-00742882⟩
  • H Ayasso, Thomas Rodet, A. Abergel. A gradient-like variational Bayesian approach for unsupervised extended emission map-making from SPIRE/Herschel data. Astronomical Data Analysis, May 2012, Cargese, France. ⟨hal-00956623⟩
  • H Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. Bayesian estimation with Gauss-Markov-Potts priors in optical diffraction tomography. SPIE Computational Imaging IX, Jan 2011, San Francisco, United States. pp9 – ID:78730U, ⟨10.1117/12.872317⟩. ⟨hal-01002340⟩
  • H Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. A variational Bayesian approach of inversion in optical diffraction tomography. 11th Workshop on Optimization and Inverse Problems in Electromagnetism (OIPE 2010), Sep 2010, Sofia, Bulgaria. pp.11-12. ⟨hal-00551747⟩
  • H Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. Une approche bayésienne en tomographie micro-onde 3D. Réunion inter-GdR Ondes-ISIS, Extraction d’information et physique des images : 5e Journée d’Imagerie Optique Non−Conventionnelle, Mar 2010, Paris, France. ⟨hal-00442200⟩
  • H Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. Approche bayésienne de l’inversion en imagerie micro-onde 3D. Les Journées d’Imagerie Optique Non-Conventionnelle, 2010, Paris, France. ⟨hal-00551753⟩
  • H Ayasso, Ali Mohammad-Djafari. Joint Image Restoration and Segmentation using Gauss-Markov-Potts Prior Models and Variational Bayesian Computation. the 15th IEEE International Conference on Image Processing, (ICIP), Nov 2009, Cairo, Egypt. pp.1297–1300. ⟨hal-00444694⟩
  • H Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. Une approche bayésienne de l’inversion en tomographie optique par diffraction. Interférences d’Ondes, Assemblée Générale du GDR Ondes, Nov 2009, Paris, France. ⟨hal-00442197⟩
  • H Ayasso, Sofia Fekih-Salem, Ali Mohammad-Djafari. Approche variationnelle bayésienne pour la reconstruction tomographique. XXIIe Colloque GRETSI – Traitement du Signal et des Images, Sep 2009, Dijon, France. ID465, 4 p. ⟨hal-00445706⟩
  • Ali Mohammad-Djafari, H Ayasso. Variational Bayes and Mean Field Approximations for Markov Field Unsupervised Estimation. IEEE International Workshop on Machine Learning for Signal Processing., Sep 2009, Grenoble, France. pp.1-6, ⟨10.1109/MLSP.2009.5306261⟩. ⟨hal-00445310⟩
  • H Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. Approche bayésienne variationnelle en reconstruction d’image en tomographie. Journées Problèmes Inverses (GDR Isis), Mar 2009, Paris, France. ⟨hal-00442208⟩
  • H Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. Imagerie micro−onde et application à la détection d’objets enfouis. Colloque Alain Bouyssy, Feb 2009, Orsay, France. ⟨hal-00442211⟩
  • H Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. A Bayesian approach to microwave imaging in a 3-D configuration. The 10th Workshop on Optimization and Inverse Problems in Electromagnetism, Sep 2008, Ilmenau, Germany. pp.180. ⟨hal-00444385⟩
  • H Ayasso, Sofia Fekih-Salem, Ali Mohammad-Djafari. Variational Bayes Approach For Tomographic Reconstruction. the 28th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, MaxEnt, Jul 2008, Sao Paulo, Brazil. pp.243–251, ⟨10.1063/1.3039006⟩. ⟨hal-00446713⟩
  • H Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. Une approche bayésienne de l’inversion en imagerie micro-onde 3D. Les Journées d’Imagerie Optique Non−Conventionnelle (GDR Ondes & GDR Isis), Mar 2008, Paris, France. ⟨hal-00444713⟩
  • H Ayasso, Ali Mohammad-Djafari. Variational Bayes with Gauss-Markov-Potts Prior Models for Joint Image Restoration and Segmentation.. The International Conference on Computer Vision Theory and Applications (VISAPP), Jan 2008, Funchal, Madeira, Portugal. pp.571-576. ⟨hal-00447517⟩

Chapitres d’ouvrage3 documents

  • Thomas Rodet, Aurélia Fraysse, Hacheme Ayasso. Variational Bayesian Approach and Bi-Model for the Reconstruction-Separation of Astrophysics Components. J.-F. Giovannelli; J. Idie. Regularization and Bayesian Methods for Inverse Problems in Signal and Image Processing, Wiley-ISTE, pp.225-249, 2015, 978-1-84821-637-2. ⟨hal-01982489⟩
  • Hacheme Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. MCMC and variational approaches for Bayesian inversion in diffraction imaging. J.-F. Giovannelli, J. Idier. Regularization and Bayesian Methods for Inverse Problems in Signal and Image Processing, Wiley-ISTE, pp.201-224, 2015, Digital signal and image processing series, 978-1-84821-637-2. ⟨hal-01262038⟩
  • Thomas Rodet, Aurélia Fraysse, Hacheme Ayasso. Approche bayésienne variationnelle et bimodèle pour la reconstruction-séparation de composantes astrophysiques. Méthodes d’inversion appliquées au traitement du signal et de l’image, Lavoisier, pp.249-273, 2013, Traité IC2, série Signal et image, 9782746245488. ⟨hal-00933592⟩

Pré-publications, Documents de travail1 document

  • H Ayasso, Ali Mohammad-Djafari. Joint Image Restoration and Segmentation using Gauss-Markov-Potts Prior Models and Variational Bayesian Computation: Technical Details. 2009. ⟨hal-00444326⟩

Rapports2 documents

  • C. Kevin Xu, Hacheme Ayasso, Alexandre Beelen, Luca Conversi, Vera Konyves, et al.. SPIRE Map-Making Test Report. [Research Report] GIPSA-LAB; IAS – Institut d’astrophysique spatiale; University of Cardiff; IAP- Institut d’astrophysique de Paris; NHSC- Caltech; University of ROMA. 2014. ⟨hal-00937747⟩
  • Hacheme Ayasso, Thomas Rodet, Alain Abergel. A Gradient-like Variational Bayesian Approach for Unsupervised Extended Emission Map-Making from SPIRE/HERSCHEL DATA. [Research Report] GIPSA-lab. 2012. ⟨hal-00765929⟩

Thèses1 document

  • H Ayasso. Une approche bayésienne de l’inversion. Application à l’imagerie de diffraction dans les domaines micro-onde et optique. Traitement du signal et de l’image [eess.SP]. Université Paris Sud – Paris XI, 2010. Français. ⟨NNT : ⟩. ⟨tel-00564015⟩

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