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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X-ray fiber diffraction may ID structural tissue changes in heart, brain

A specialized x-ray diffraction lab at the Illinois Institute of Technology (IIT) in Chicago is using fiber diffraction, allowing scientists to study structural tissue changes in the human heart, brain and even dinosaur fossils. The technique may help physicians track injury-related tissue damage and identify risk areas, according to an American Crystallographic Association release from July 22.

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Q&A: New Zealand father, son scientists discuss development of 3D color x-ray scanner

Health Imaging recently spoke with father-and-son scientists Anthony Butler, PhD, and Phil Butler, PhD, about the MARS spectral x-ray scanner, a new 3D color x-ray machine that has gained international attention since it successfully imaged its first human subject last week.

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Q&A: Sham Sokka on how radiologists can leverage AI to minimize patient no-shows

Sham Sokka, PhD, has spent the bulk of his career in radiology, where he’s worked for 15 years with a range of clients to shape and customize imaging modalities, workflows and software.

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IBM Watson, VA extend precision oncology AI partnership through 2019

The U.S. Department of Veterans Affairs (VA) and IBM Watson Health have extended their partnership leveraging artificial intelligence (AI) to help analyze cancer data in veterans with the disease.

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Show me the money: Who will foot the AI bill? And how?

Artificial intelligence (AI) has the potential to revolutionize patient-care and serve as a valuable tool for radiologists. But with all its promise, a recent editorialist asked: Has anyone thought about how it will all be paid for? And by whom?

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Brian MRI technique may predict disabilities in MS patients by measuring iron levels

The MRI-based technique of quantitative susceptibility mapping can monitor iron levels in the brains of multiple sclerosis (MS) patients, allowing physicians to identify those at a higher risk of developing physical disability, according to a recent Radiology study.  

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AI research on photo quality could work wonders for medical imaging

Researchers have shown that they can use artificial intelligence (AI) to restore low-quality photos by exposing a neural network to only other low-quality photos, according to work presented at the International Conference on Machine Learning in Stockholm.

3D MRI may surpass 2D for detecting knee cartilage defects

Technological advancements over the past three decades have placed 3D MRI on par with its 2D counterpart in depicting cartilage defects, according to a study published in Radiology. With specific alterations, the modality may be able to replace traditional MRI.