Artificial Intelligence

Artificial intelligence (AI) is becoming a crucial component of healthcare to help augment physicians and make them more efficient. In medical imaging, it is helping radiologists more efficiently manage PACS worklists, enable structured reporting, auto detect injuries and diseases, and to pull in relevant prior exams and patient data. In cardiology, AI is helping automate tasks and measurements on imaging and in reporting systems, guides novice echo users to improve imaging and accuracy, and can risk stratify patients. AI includes deep learning algorithms, machine learning, computer-aided detection (CAD) systems, and convolutional neural networks. 

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Top performing PACS companies based on user feedback

Agfa and Sectra both performed well with end-user satisfaction scores in the 2025 Best in KLAS list of radiology IT systems.

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How do radiologists feel about utilizing GPT-4 in practice?

In recent years, there has been much talk of the potential for large language models to improve radiology workflows.

AI-based 3D CTA reconstruction solution scores FDA clearance

Using the new solution, CTA recons are completed in a matter of minutes, not hours.

Nina Kottler, MD, Radiology Partners, offers overview of the U.S. AI regulatory landscape as government and radiologists work on ways to ensure artificial intelligence is not bias and works properly.

Overview of the regulatory landscape of AI in radiology

Nina Kottler, MD, associate CMO for clinical AI at Radiology Partners, explains the movement toward greater regulation of artificial intelligence and the need to test for bias. 

Medical imaging trends to watch in 2025

The healthcare market analysis firm Signify Research released a list of predictions in radiology its analysts expect to see in 2025. 

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GPT-4 helps ensure recommendations for additional imaging aren't overlooked in reports

Recommendations for additional imaging are routinely included in radiology reports but are sometimes overlooked or not communicated in a timely manner. Experts believe large language models can help address these lapses in care. 

GPT-4 can proofread radiology reports for a penny apiece

Researchers estimate that it could cost less than $0.01 per report to use the large language model as a radiology report proofreader. 

DL model identifies and segments lung tumors on CT scans.

Deep learning model halves lung tumor segmentation times

In a new clinical study, the model was able to maintain its performance on scans completed on different types of CT equipment across multiple medical centers.  

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GE HealthCare launches new cardiac CT scanner with advanced AI capabilities

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Bracco updates HeartSee coronary flow capacity software with new diagnostic features

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Key trends in diagnostic heart testing: CT on the rise as some traditional techniques fall out of favor

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