Current State of Community-Driven Radiological AI Deployment in Medical Imaging
These videos have been matched automatically. Contact us if they are not relevant.
These videos have been matched automatically. Contact us if they are not relevant.
View abstract on PubMed
Summary
This summary is machine-generated.Artificial intelligence (AI) can enhance medical imaging efficiency, but clinical translation faces challenges. This paper explores AI in radiology workflows and introduces the Medical Open Network for AI (MONAI) to bridge the gap.
Area Of Science
- Medical Imaging
- Artificial Intelligence
- Radiology Workflow
Background
- Radiologist workload is increasing due to growing medical imaging data.
- AI shows potential to improve medical image analysis efficiency.
- A gap exists between AI research and clinical application in radiology.
Purpose Of The Study
- Provide an overview of AI in medical imaging.
- Highlight the importance of standards in radiology workflows.
- Identify challenges in deploying AI in clinical settings.
Main Methods
- Examined current radiology workflows and AI implementation challenges.
- Developed a taxonomy of AI use cases with real-world integration examples.
- Introduced the Medical Open Network for AI (MONAI) as a solution.
Main Results
- Identified significant hurdles in integrating AI into hospital radiology workflows.
- Demonstrated practical AI integration examples within hospitals.
- Proposed MONAI as a tool for reproducible deep learning solutions.
Conclusions
- Addressing AI implementation challenges requires standardized approaches.
- MONAI offers a framework for successful AI integration in radiology.
- Bridging the research-to-clinical translation gap is crucial for AI adoption.
These videos have been matched automatically. Contact us if they are not relevant.
These videos have been matched automatically. Contact us if they are not relevant.
Related Concept Videos
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
Positron emission tomography (PET) is a medical imaging technique involving radiopharmaceuticals — substances that emit short-lived radiation. Although the first PET scanner was introduced in 1961, it took 15 more years before radiopharmaceuticals were combined with the technique and revolutionized its potential.
One of the main requirements of a PET scan is a positron-emitting radioisotope, which is produced in a cyclotron and then attached to a substance used by the part of the body...
Radiological investigations, including X-rays and computed tomography (CT) scans, are critical for diagnosing and evaluating various medical conditions. These imaging techniques provide valuable insights into the body's internal structures, aiding in the detection of abnormalities, assessment of disease progression, and development of treatment strategies. This article delves into two primary radiological investigations, chest X-rays and CT scans, outlining their purpose, procedures, and...