14 citations · 21 across the 3 of their papers we have counts for
3 papers · 1 filter
Weakly-supervised Learning For Catheter Segmentation in 3D Frustum Ultrasound
Hongxu Yang, Caifeng Shan, Alexander F. Kolen +1
Accurate and efficient catheter segmentation in 3D ultrasound (US) is essential for cardiac intervention. Currently, the state-of-the-art segmentation algorithms are based on convo…
Medical Instrument Detection in Ultrasound-Guided Interventions: A Review
Hongxu Yang, Caifeng Shan, Alexander F. Kolen +1
Medical instrument detection is essential for computer-assisted interventions since it would facilitate the surgeons to find the instrument efficiently with a better interpretation…
Deep Q-Network-Driven Catheter Segmentation in 3D US by Hybrid Constrained Semi-Supervised Learning and Dual-UNet
Hongxu Yang, Caifeng Shan, Alexander F. Kolen +1
Catheter segmentation in 3D ultrasound is important for computer-assisted cardiac intervention. However, a large amount of labeled images are required to train a successful deep co…