Intrathoracic airway segmentation in computed tomography (CT) is a
prere...
Natural language generation is one of the most impactful fields in NLP, ...
Open international challenges are becoming the de facto standard for
ass...
Although recent deep learning methods, especially generative models, hav...
The radiation dose in computed tomography (CT) examinations is harmful f...
Detailed pulmonary airway segmentation is a clinically important task fo...
Magnetic resonance imaging serves as an essential tool for clinical
diag...
Parallel Imaging (PI) is one of the most im-portant and successful
devel...
Recent evolution in deep learning has proven its value for CT-based lung...
Purpose: Bronchoscopic intervention is a widely-used clinical technique ...
Airway segmentation is critical for virtual bronchoscopy and computer-ai...
The integration of compressed sensing and parallel imaging (CS-PI) provi...
Magnetic resonance imaging (MRI) is a widely used medical imaging modali...
3D Convolutional Neural Networks (CNNs) have been widely adopted for air...
This work presents an unsupervised deep learning scheme that exploiting
...
This paper proposes an iterative generative model for solving the automa...
To improve the compressive sensing MRI (CS-MRI) approaches in terms of f...
Compressive sensing is an impressive approach for fast MRI. It aims at
r...