1 code implementation • 24 Jan 2024 • Ruben T. Lucassen, Willeke A. M. Blokx, Mitko Veta
Our results demonstrate that the proposed model can accurately segment H&E stained tissue cross-sections and pen markings in WSIs while being robust to many common slide and scanning artifacts.
1 code implementation • 15 Feb 2023 • Ruben T. Lucassen, Mohammad H. Jafari, Nicole M. Duggan, Nick Jowkar, Alireza Mehrtash, Chanel Fischetti, Denie Bernier, Kira Prentice, Erik P. Duhaime, Mike Jin, Purang Abolmaesumi, Friso G. Heslinga, Mitko Veta, Maria A. Duran-Mendicuti, Sarah Frisken, Paul B. Shyn, Alexandra J. Golby, Edward Boyer, William M. Wells, Andrew J. Goldsmith, Tina Kapur
B-line artifacts in LUS videos are key findings associated with pulmonary congestion.
no code implementations • 15 Feb 2021 • Friso G. Heslinga, Ruben T. Lucassen, Myrthe A. van den Berg, Luuk van der Hoek, Josien P. W. Pluim, Javier Cabrerizo, Mark Alberti, Mitko Veta
In this research, deep learning is used to automatically delineate the corneal interfaces and measure corneal thickness with high accuracy in post-DMEK AS-OCT B-scans.