Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer in whi...
Lung cancer is a leading cause of death worldwide and early screening is...
Liver tumor segmentation and classification are important tasks in compu...
Gastric cancer is the third leading cause of cancer-related mortality
wo...
Liver cancer has high morbidity and mortality rates in the world. Multi-...
In this paper, we consider the scenario-based two-stage stochastic DC op...
Real-world medical image segmentation has tremendous long-tailed complex...
Pancreatic cancer is one of the leading causes of cancer-related death.
...
Verified compositional compilation (VCC) is a notion of modular verifica...
Human readers or radiologists routinely perform full-body multi-organ
mu...
Lymph node (LN) metastasis status is one of the most critical prognostic...
Time series anomaly detection strives to uncover potential abnormal beha...
Manually annotating complex scene point cloud datasets is both costly an...
Using deep neural networks to predict the solutions of AC optimal power ...
In this paper, we propose a novel two-stage context-aware network named ...
Modeling and simulating a power distribution network (PDN) for printed
c...
Reduction in the cost of Network Cameras along with a rise in connectivi...
The pancreatic disease taxonomy includes ten types of masses (tumors or
...
Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancer...
Accurate and automated tumor segmentation is highly desired since it has...
Deep neural network (DNN) based approaches have been widely investigated...
Most of the existing self-supervised feature learning methods for 3D dat...
The success of supervised learning requires large-scale ground truth lab...
Residual images and illumination estimation have been proved very helpfu...
Annotation of medical images has been a major bottleneck for the develop...
In this paper we propose an attentive recurrent generative adversarial
n...
Radiogenomic map linking image features and gene expression profiles is
...
Recent advances in deep learning for medical image segmentation demonstr...
To alleviate the cost of collecting and annotating large-scale point clo...
Prognostic tumor growth modeling via medical imaging observations is a
c...
Simulating the dynamic characteristics of a PN junction at the microscop...
Fine-grained classification of cervical cells into different abnormality...
Automation-assisted cervical screening via Pap smear or liquid-based cyt...
This paper reports Deep LOGISMOS approach to 3D tumor segmentation by
in...
Image segmentation is a fundamental problem in medical image analysis. I...
Tumor growth is associated with cell invasion and mass-effect, which are...
Radiologists in their daily work routinely find and annotate significant...
Tumor growth prediction, a highly challenging task, has long been viewed...