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Rodrigue de Schaetzen
Rodrigue de Schaetzen
Graduate Student, University of Waterloo
Verified email at uwaterloo.ca - Homepage
Title
Cited by
Cited by
Year
Convolutional neural network with a hybrid loss function for fully automated segmentation of lymphoma lesions in FDG PET images
F Yousefirizi, N Dubljevic, S Ahamed, I Bloise, C Gowdy, Y Farag, ...
Medical Imaging 2022: Image Processing 12032, 214-220, 2022
52022
Real-Time Navigation for Autonomous Surface Vehicles In Ice-Covered Waters
R de Schaetzen, A Botros, R Gash, K Murrant, SL Smith
2023 IEEE International Conference on Robotics and Automation (ICRA), 1069-1075, 2023
32023
A fully automated method for bladder segmentation in PSMA PET/CT scans
Y Farag, R de Schaetzen, G Chausse, F Yousefirizi, I Klyuzhin, A Rahmim, ...
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING 48 (SUPPL 1 …, 2021
12021
Exploring Machine Learning Models to Improve the Classification of Displaced Hadronic Jets in the ATLAS Calorimeter
R de Schaetzen
University of British Columbia, 2020
12020
Efficient Ground Vehicle Path Following in Game AI
R de Schaetzen, A Sestini
2023 IEEE Conference on Games (CoG), 2023
2023
A Fully Automated Method for Prostate Segmentation in PSMA PET/CT Scans
R De Schaetzen, Y Farag, G Chaussé, A Rahmim, F Yousefirizi, C Uribe
Journal of Nuclear Medicine 64 (supplement 1), P1193-P1193, 2023
2023
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