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Journal Article

  1. [VIND-23a]“Guided Deep Embedded Clustering regularization for multi-feature medical signal classification”, Pattern Recognition, vol. 143, 2023.PDF icon Vindas-23_PR_Guided deep embedded clustering regularization for multifeature classif.pdf (3.01 MB)
  2. [VIND-22a]“Semi-automatic data annotation based on feature-space projection and local quality metrics: an application to cerebral emboli characterization”, Medical Image Analysis, 2022.PDF icon Vindas-22_Media_Semi_supervised_Data_Annotation.pdf (13.46 MB)
  3. [ROUX-18]“Experimental 3-D Ultrasound Imaging with 2-D Sparse Arrays using Focused and Diverging Waves”, Scientific Reports, vol. 8, 2018.
    https://www.nature.com/articles/s41598-018-27490-2
  4. [GASS-17]“High-Quality Plane Wave Compounding using Convolutional Neural Networks”, IEEE Transactions on Ultrasonics, Ferroelectricity and Frequency Control, vol. 64, pp. 1637-1639, 2017.
  5. [ROUX-17]“Wideband 2D array design optimization with fabrication constraints for 3D US imaging”, IEEE Transactions on Ultrasonics Ferroelectrics an Frequency Control, vol. 64, 2017.
    http://ieeexplore.ieee.org/document/7581110/
  6. [ROUX-16]“2D Ultrasound Sparse Arrays Multi-Depth Radiation Optimization Using Simulated Annealing and Spiral-Array Inspired Energy Functions”, IEEE Transactions on Ultrasonics Ferroelectrics an Frequency Control, vol. 63, 2016.
    http://ieeexplore.ieee.org/document/7549037/

Conference Paper

  1. [VIND-23b]“Soft-labels noise tolerant loss functions for transcranial Doppler ultrasound signal classification”, in IEEE Ultrasonics symposium, 2023, pp. 1-4.PDF icon Vindas-23_IEEE-IUS_Soft labels noise tolerant loss functions for TCD signal classification.pdf (632.81 KB)
  2. [VIND-23c]“Deep Embedded Clustering regularization for supervised imbalanced cerebral emboli classification using transcranial Doppler ultrasound”, in 31st European Signal Processing Conference (EUSIPCO 2023), september 4-8, Helsinki, Finland, 2023.PDF icon Vindas-23_Eusipco_DEC regularization for supervised imbalanced cerebral emboli classification using TDC.pdf (392.52 KB)
  3. [VIND-22b]“An hybrid CNN-Transformer model based on multi-feature extraction and attention fusion mechanism for classification of medical signals”, in Machine Learning for Healthcare, 2022.
    https://static1.squarespace.com/static/59d5ac1780bd5ef9c396eda6/t/62e97636b9962e1079555986/1659467321416/43+Paper-43_CameraReady.pdf
  4. [VIND-21]“Semi-supervised annotation of Transcranial Doppler ultrasound micro-embolic data”, in IEEE International Ultrasonics Symposium, 2021.PDF icon Vindas-21_IUS_Semi-supervised annotation of Transcranial Doppler.pdf (1.84 MB)
  5. [MATE-18a]“Optimal virtual sources distribution in 3-D diverging wave US imaging”, in IEEE International Ultrasonics Symposium, Kobe, Japan, 2018.
  6. [MATT-18b]“Specral Doppler measurments with 2D sparse arrays”, in IEEE International Ultrasonics Symposium, Kobe, Japan, 2018.
  7. [ROUX-17b]“3D diverging waves with 2D sparse arrays: a feasibility study”, in IEEE International Ultrasonics Symposium, Washington, USA, 2017.
  8. [ROUX-17c]“Validation of optimal 2D sparse arrays in focused mode phantom experiments”, in IEEE International Ultrasonics Symposium, Washington, USA, 2017.
  9. [DIAR-16]“Comparison of different optimized irregular sparse 2D ultrasound arrays ”, in IEEE International Ultrasonics Symposium, Tours, France., 2016, pp. 1-4.
    http://ieeexplore.ieee.org/document/7728414/
  10. [ROUX-15c]E. Roux, Robini, M., Ramalli, A., Tortoli, P., C., C., and Liebgott, H., “Modélisation et simulation acoustique pour l’optimisation de sondes échographiques 2D par recuit simulé”, in GRETSI, 2015, p. accepted.
    https://hal.archives-ouvertes.fr/hal-01286079/
  11. [ROUX-15a]E. Roux, Ramalli, A., Tortoli, P., Cachard, C., Robini, M., and Liebgott, H., “Speed-Up of Acoustic Simulation Techniques for 2D Sparse Array Optimization by Simulated Annealing”, in IEEE International Ultrasonics Symposium, 2015, pp. 1–4.
    http://ieeexplore.ieee.org/document/7329330/
  12. [ROUX-15b]E. Roux, Ramalli, A., Robini, M., Liebgott, H., C., C., and Tortoli, P., “Spiral Array Inspired Multi-Depth Cost Function for 2D Sparse Array Optimization”, in IEEE International Ultrasonics Symposium, 2015, pp. 1-4.
    http://ieeexplore.ieee.org/document/7329187/
  13. [DIAR-14]B. Diarra, Robini, M., Roux, E., Tortoli, P., Liebgott, H., and Cachard, C., “Optimization of free-moving elements in 2D ultrasound sparse arrays”, in IEEE International Ultrasonics Symposium, Chicago, Illinois, USA, 2014, pp. 2189–2192.
    http://ieeexplore.ieee.org/document/6931734/
  14. [ROUX-14]E. Roux, Diarra, B., Robini, M., Cachard, C., Tortoli, P., and Liebgott, H., “Realistic acoustic simulation of 2D probe elements in simulated annealing sparse array optimization”, in IEEE International Ultrasonics Symposium, Chicago, Illinois, USA, 2014, pp. 2125–2128.
    http://ieeexplore.ieee.org/document/6931817/

Thesis

  1. [ROUX-16]“2D sparse array optimization and operating strategy for real-time 3D ultrasound imaging”, Claude Bernard Lyon 1 , Lyon, 2016.
    https://tel.archives-ouvertes.fr/tel-01451208/document

Miscellaneous

  1. [ROUX-15d]E. Roux, Ramalli, A., Tortoli, P., Robini, M., Liebgott, H., and Cachard, C., “Optimisation du rayonnement acoustique de sondes parcimonieuses pour l’échographie 3D temps-réel”. p. accepted, 2015.