92 citations · 121 across the 6 of their papers we have counts for
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Adaptive Multi-scale Online Likelihood Network for AI-assisted Interactive Segmentation
Muhammad Asad, Helena Williams, Indrajeet Mandal +4
Existing interactive segmentation methods leverage automatic segmentation and user interactions for label refinement, significantly reducing the annotation workload compared to man…
Partial supervision for the FeTA challenge 2021
Lucas Fidon, Michael Aertsen, Suprosanna Shit +4
This paper describes our method for our participation in the FeTA challenge2021 (team name: TRABIT). The performance of convolutional neural networks for medical image segmentation…
Interactive Segmentation via Deep Learning and B-Spline Explicit Active Surfaces
Helena Williams, João Pedrosa, Laura Cattani +4
Automatic medical image segmentation via convolutional neural networks (CNNs) has shown promising results. However, they may not always be robust enough for clinical use. Sub-optim…
CA-Net: Comprehensive Attention Convolutional Neural Networks for Explainable Medical Image Segmentation
Ran Gu, Guotai Wang, Tao Song +6
Accurate medical image segmentation is essential for diagnosis and treatment planning of diseases. Convolutional Neural Networks (CNNs) have achieved state-of-the-art performance f…
Uncertainty-Guided Efficient Interactive Refinement of Fetal Brain Segmentation from Stacks of MRI Slices
Guotai Wang, Michael Aertsen, Jan Deprest +3
Segmentation of the fetal brain from stacks of motion-corrupted fetal MRI slices is important for motion correction and high-resolution volume reconstruction. Although Convolutiona…
Deep Sequential Mosaicking of Fetoscopic Videos
Sophia Bano, Francisco Vasconcelos, Marcel Tella Amo +7
Twin-to-twin transfusion syndrome treatment requires fetoscopic laser photocoagulation of placental vascular anastomoses to regulate blood flow to both fetuses. Limited field-of-vi…