26 citations · 166 across the 36 of their papers we have counts for
7 papers · 1 filter
Translating Simulation Images to X-ray Images via Multi-Scale Semantic Matching
Jingxuan Kang, Tudor Jianu, Baoru Huang +4
Endovascular intervention training is increasingly being conducted in virtual simulators. However, transferring the experience from endovascular simulators to the real world remain…
3D-UCaps: 3D Capsules Unet for Volumetric Image Segmentation
Tan Nguyen, Binh-Son Hua, Ngan Le
Medical image segmentation has been so far achieving promising results with Convolutional Neural Networks (CNNs). However, it is arguable that in traditional CNNs, its pooling laye…
CapsNet for Medical Image Segmentation
Minh Tran, Viet-Khoa Vo-Ho, Kyle Quinn +3
Convolutional Neural Networks (CNNs) have been successful in solving tasks in computer vision including medical image segmentation due to their ability to automatically extract fea…
SS-3DCapsNet: Self-supervised 3D Capsule Networks for Medical Segmentation on Less Labeled Data
Minh Tran, Loi Ly, Binh-Son Hua +1
Capsule network is a recent new deep network architecture that has been applied successfully for medical image segmentation tasks. This work extends capsule networks for volumetric…
DAM-AL: Dilated Attention Mechanism with Attention Loss for 3D Infant Brain Image Segmentation
Dinh-Hieu Hoang, Gia-Han Diep, Minh-Triet Tran +1
While Magnetic Resonance Imaging (MRI) has played an essential role in infant brain analysis, segmenting MRI into a number of tissues such as gray matter (GM), white matter (WM), a…
Offset Curves Loss for Imbalanced Problem in Medical Segmentation
Ngan Le, Trung Le, Kashu Yamazaki +3
Medical image segmentation has played an important role in medical analysis and widely developed for many clinical applications. Deep learning-based approaches have achieved high p…