most citedAnnotation-Efficient Learning for Medical Image Segmentation based on Noisy Pseudo Labels and Adversarial Learning

36 citations · 69 across the 3 of their papers we have counts for

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eess.IV2021

2020 CATARACTS Semantic Segmentation Challenge

Imanol Luengo, Maria Grammatikopoulou, Rahim Mohammadi +37

Surgical scene segmentation is essential for anatomy and instrument localization which can be further used to assess tissue-instrument interactions during a surgical procedure. In…

eess.IV2020★ 36 cited

Annotation-Efficient Learning for Medical Image Segmentation based on Noisy Pseudo Labels and Adversarial Learning

Lu Wang, Dong Guo, Guotai Wang +1

Despite that deep learning has achieved state-of-the-art performance for medical image segmentation, its success relies on a large set of manually annotated images for training tha…