Thomas Marini
@thomasmarini11
University of Rochester Medical Center
Radiologist
ID: 1379970905913327619
08-04-2021 01:35:53
111 Tweet
79 Followers
134 Following
This sweep is similar to previously published work by Thomas Marini et al (clinicalimagingscience.org/lung-ultrasoun…), but is exciting because it potentially represents an entirely new paradigm for Lung #POCUS
We hope the editorial captures our read of this and how it fits into the existing literature. I'm personally just excited at the chance to get to write with the always insightful Segun Olusanya (He/Him) [email protected] about how to advance this useful imaging modality. sciencedirect.com/science/articl…
@URMC_Imaging is thrilled to see the research using Butterfly Network iQ+ devices, conducted by Thomas Marini and our team has been recently featured by Forbes.
Ultrasound, AI method diagnoses breast lumps without experts via AuntMinnie.com auntminnie.com/index.aspx?sec…
Congratulations, Thomas Marini on your recent AuntMinnie.com publication on Ultrasound, AI method diagnoses breast lumps without experts! #Radiology #Ultrasound University of Rochester Medicine
Important innovative work. Great to have been part of this team. Kudos to Thomas Marini for his leadership and perseverance!
This 8-step protocol for inexperienced operators has the potential to improve access to obstetric ultrasonography globally. #GlobalHealth #Radiology Thomas Marini Tim Baran Jennifer Harvey University of Rochester Medicine @URMC_Imaging
Great new work by Jonah Kan Thomas Marini Galen Brennan Tim Baran et al URMC Imaging ECE at University of Rochester University of Rochester - 'WATUNet: a deep #neuralnetwork for segmentation of volumetric sweep #imaging #ultrasound' - iopscience.iop.org/article/10.108… #machinelearning #radiology #cancer #oncology #health
WATUNet: a deep neural network for segmentation of volumetric sweep imaging ultrasound doi.org/10.1088/2632-2… via Machine Learning: Science and Technology
Most people in the world lack access to medical imaging including for assessment of pulmonary disease. Researchers from The Hajim School and UR Medicine are using #AI to develop a system that rapidly triages pulmonary disease without a radiologist or sonographer #URochesterResearch