Emphasis
The emphasis is on development of transformative machine intelligence-based systems, emerging tools, and modern technologies for diagnosing and recommending treatments for a range of diseases and health conditions. Unsupervised and semi-supervised techniques and methodologies are of particular interest.
Program priorities and areas of interest:
- clinical decision support systems
- computer-aided diagnosis
- computer-aided screening
- analyzing complex patterns and images
- screening for diseases
- natural-language processing and understanding
- medical decision-making
- predictive modeling
- computer vision
- robotic and image guided surgery
- personalized imaging and treatment
- drug discovery
- radiomics
- machine/deep learning-based segmentation, registration, etc.
Additional support
This program also supports:
- early-stage development of software, tools, and reusable convolutional neural networks
- data reduction, denoising, improving performance (health-promoting apps), and deep-learning based direct image reconstruction
- approaches that facilitate interoperability among annotations used in image training databases
Related News
"We didn't," says Dr. Carlo Pierpaoli, chief of the NIH's laboratory on quantitative medical imaging. The NIH study was larger, Pierpaoli says, and used a control group that was better matched — in terms of age, profession, and location — to the group being studied. It also was designed to produce highly consistent results.
Source: NPR
Researchers have developed a new catheter-based device that combines two powerful optical techniques to image the dangerous plaques that can build up inside the arteries that supply blood to the heart. By providing new details about plaque, the device could help clinicians and researchers improve treatments for preventing heart attacks and strokes.
Source: Optica Publishing Group