20 citations · 68 across the 7 of their papers we have counts for
15 papers · 1 filter
Volumetric Medical Image Segmentation: A 3D Deep Coarse-to-fine Framework and Its Adversarial Examples
Yingwei Li, Zhuotun Zhu, Yuyin Zhou +4
Although deep neural networks have been a dominant method for many 2D vision tasks, it is still challenging to apply them to 3D tasks, such as medical image segmentation, due to th…
Domain Adaptive Relational Reasoning for 3D Multi-Organ Segmentation
Shuhao Fu, Yongyi Lu, Yan Wang +4
In this paper, we present a novel unsupervised domain adaptation (UDA) method, named Domain Adaptive Relational Reasoning (DARR), to generalize 3D multi-organ segmentation models t…
Deep Distance Transform for Tubular Structure Segmentation in CT Scans
Yan Wang, Xu Wei, Fengze Liu +5
Tubular structure segmentation in medical images, e.g., segmenting vessels in CT scans, serves as a vital step in the use of computers to aid in screening early stages of related d…
FusionNet: Incorporating Shape and Texture for Abnormality Detection in 3D Abdominal CT Scans
Fengze Liu, Yuyin Zhou, Elliot Fishman +1
Automatic abnormality detection in abdominal CT scans can help doctors improve the accuracy and efficiency in diagnosis. In this paper we aim at detecting pancreatic ductal adenoca…
Prior-aware Neural Network for Partially-Supervised Multi-Organ Segmentation
Yuyin Zhou, Zhe Li, Song Bai +5
Accurate multi-organ abdominal CT segmentation is essential to many clinical applications such as computer-aided intervention. As data annotation requires massive human labor from…
Thickened 2D Networks for Efficient 3D Medical Image Segmentation
Qihang Yu, Yingda Xia, Lingxi Xie +2
There has been a debate in 3D medical image segmentation on whether to use 2D or 3D networks, where both pipelines have advantages and disadvantages. 2D methods enjoy a low inferen…