Although deep neural networks have been a dominant method for many 2D vi...
Determining the spread of GTV_LN is essential in defining the respective...
Finding, identifying and segmenting suspicious cancer metastasized lymph...
Although having achieved great success in medical image segmentation, de...
Finding and identifying scatteredly-distributed, small, and critically
i...
OAR segmentation is a critical step in radiotherapy of head and neck (H ...
This work presents comprehensive results to detect in the early stage th...
Deep learning algorithms, in particular 2D and 3D fully convolutional ne...
We propose a novel framework, uncertainty-aware multi-view co-training
(...
This paper proposes an intuitive approach to finding pancreatic ductal
a...
There has been a debate on whether to use 2D or 3D deep neural networks ...
In this paper, we adopt 3D CNNs to segment the pancreas in CT images.
Al...
While recent deep neural networks have achieved a promising performance ...
Multi-instance learning (MIL) has a wide range of applications due to it...
Multiple-instance learning (MIL) has served as an important tool for a w...
We study the problem of how to build a deep learning representation for ...