Emphasis
The emphasis is on using image data to achieve better health outcomes and smarter health care. Examples of technology development areas in this program include but are not limited to models, algorithms, software, methodologies, and other tools that will: facilitate medical imaging research; support clinical detection, diagnosis and therapy; and improve patient healthcare.
Program priorities and areas of interest:
- Image segmentation, image registration, atlas generation, image fusion, morphometry measurement, and the determination of function and structure from medical images
- Diagnostic-performance evaluation, computer-aided diagnosis, statistical models for evaluation of observer performance, and assessment of observer variability
- Quantitative imaging and image-based biomarkers
- Image-driven computer-aided diagnosis and decision support systems
- Virtual reality technologies
- Dose estimation and reduction software
Additional support
This program also supports:
- Early-stage validation of tools for image processing, visual perception and display
- Tools to assess image quality and observer performance
- Tools and software that enable large-scale, longitudinal and/or multi-site imaging studies and clinical trials
- Medical imaging mobile apps for early detection
Related News
Brain cancer is the second most common cancer in children after leukemia, and it is also the deadliest, due to the fact that brain tumors are diverse, resistant to treatments and often hard to access surgically. A collaborative team of researchers at several institutions have developed a new way to profile brain cancers in children, paving the way for improved diagnostics and treatments. Source: UTSA Today
The National Institutes of Health (NIH) has selected four finalists with innovative, non-invasive technologies that seek to improve diagnosis of endometriosis.
Researchers are developing an AI tool to evaluate placental photographs that could provide predictions for multiple adverse outcomes, such as infection or sepsis.
NIH has awarded more than $4 million in funds and support services to three diagnostic technology developers as part of RADx ® Tech’s Advanced Platforms for HIV Viral Load Monitoring program.
A tiny, four-fingered “hand” folded from a single piece of DNA can pick up the virus that causes COVID-19 for highly sensitive rapid detection and can even block viral particles from entering cells to infect them, University of Illinois Urbana-Champaign researchers report. Source: University of Illinois Urbana-Champaign News Bureau