RSENSE publications

Peer-Reviewed Publications
  • Stylogiannis, A.; Prade, L.; Glasl, S.; Mustafa, Q.; Zakian, C.; Ntziachristos, V. Frequency wavelength multiplexed optoacoustic tomography. Nature Comm. 2022, 13, 4488. https://doi.org/10.1038/s41467-022-32175-6
  • Dehner, C.; Olefir, I.; Chowdhury, K. B.; Jüstel, D.; Ntziachristos, V. Deep-Learning-Based Electrical Noise Removal Enables High Spectral Optoacoustic Contrast in Deep Tissue. IEEE 2022, 41 (11), 3182 – 3193, https://doi.org/10.1109/TMI.2022.3180115
  • Stylogiannis, A.; Kousias, N.; Kontses, A.; Ntziachristos, L.; Ntziachristos, V. A Low-Cost Optoacoustic Sensor for Environmental Monitoring. Sensors 2021, 21, 1379. https://doi.org/10.3390/s21041379
  • Waibel, D. J. E.;  Boushehri, S. S.; Marr, C. InstantDL: an easy-to-use deep learning pipeline for image segmentation and classification. BMC Bioinformatics 2021, 22, 103. https://doi.org/10.1186/s12859-021-04037-3
  • Stylogiannis, A.; Riobo, L.; Prade, L.; Glasl, S.; Klein, S.; Lucidi, G.; Fuchs, M.; Saur, D.; Ntziachristos, V. “Low-cost single-point optoacoustic sensor for spectroscopic measurement of local vascular oxygenation,” Opt. Lett. 2020, 45, 6579-6582, https://doi.org/10.1364/OL.412034
Preprints
  • Dehner, C.; Olefir, I.; Chowdhury, K. B.; Jüstel, D.; Ntziachristos, V. (2021). Deep learning based electrical noise removal enables high spectral optoacoustic contrast in deep tissue. arXiv preprint arXiv:2102.12960.

  • Waibel, D.; Boushehri, S. S.; Marr, C. “InstantDL – An easy-to-use deep learning pipeline for image segmentation and classification” bioRxiv 2020.06.22.164103; doi: https://doi.org/10.1101/2020.06.22.164103