Thrilled to announce that @stephenalexlee and Paul Xing, two members from our lab, led by @JeanProvost at @polymtl, will present their latest research at #ISBI2024 in Athens this week! 🇬🇷

🍁Excited to share that 8 members of our lab, directed by @JeanProvost in @polymtl, will be presenting their latest work at #IUS2023 in Montréal 🇨🇦 next week. Hope to see you there @ieeeius

📢 Alexis Leconte, étudiant à la maîtrise au @ProvostLab @polymtl, est l'un des finalistes du concours de l'@_Acfas "La preuve par l'image" #LPPI ! Vous pouvez voter pour son image, "Les vaisseaux du souvenir", pour le Prix du public @DecouverteRC : tinyurl.com/mph6c5nd

Si vous souhaitez en savoir plus sur comment l'on peut obtenir des images du flux sanguin dans de minuscules vaisseaux par imagerie ultrasonore, c'est par ici ! Merci @Scilabus pour ta visite dans notre laboratoire @polymtl ! youtube.com/watch?v=5VxaoK36…

See you next year in Montreal for #ius2023 @ieeeius!

Chloé (@ChloeBourquin) presented how Kalman filtering could help to perform quantitative pulsatility measurements in the whole brain using 3D Dynamic Ultrasound Localization Microscopy (3D DULM) 🐱 Her work was part of the highlights of the conference.

Alice (@alice_wu96) works with the RCA probe: she showed that SMIF beamforming performed better than DAS in vitro and tested both methods in vivo on a mouse brain in 3D 🐭

Michael showed how to perform Ultrasound Localization Microscopy (ULM) with ultrafast harmonic imaging in vitro. This method results in the detection of slower microbubbles, with a better resolution (x2) and CNR (+4dB).

Olivier proposed an original technique to form an ultrasound image with a single element, using an ultrasound probe combined with an ergodic relay.

Samuel showed how using an additional transducer to modulate microbubbles signal can help isolate the microbubbles from the clutter. This may provide an efficient way to detect slow microbubbles that are often removed by commonly used clutter filters 🫧

Paul presented a new method for aberration correction in ULM. Using a minimization approach based on the Fréchet derivative of the forward imaging operator, he could estimate the aberration function to obtain a vasculature map with ↗️ image quality through the mouse skull in vivo

Brice @RaubyB (co-supervised by @Mila_Quebec) proposed a Sparse Tensor Neural Network to reconstruct the path of the microbubbles and tested it in silico in 3D and in vivo in 2D+t. This method could help to retrieve the blood flow dynamics in microvessels.