40 citations · 46 across the 3 of their papers we have counts for
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eess.IV2022★ 6 cited
Learning deep abdominal CT registration through adaptive loss weighting and synthetic data generation
Javier Pérez de Frutos, André Pedersen, Egidijus Pelanis +5
Purpose: This study aims to explore training strategies to improve convolutional neural network-based image-to-image deformable registration for abdominal imaging. Methods: Differe…
eess.IV2020★ 40 cited
Towards a Video Quality Assessment based Framework for Enhancement of Laparoscopic Videos
Zohaib Amjad Khan, Azeddine Beghdadi, Faouzi Alaya Cheikh +6
Laparoscopic videos can be affected by different distortions which may impact the performance of surgery and introduce surgical errors. In this work, we propose a framework for aut…