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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Risk estimation algorithm reduces noise in MR images

Pairing the established denoising algorithm NeighShrink with chi-square unbiased risk estimation (CURE) was superior to conventional methods at reducing noise in MR images, reported researchers of a study published in Artificial Intelligence in Medicine.

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3D ultrasound helps radiation oncologists treat gynecological cancers

International researchers have created a new ultrasound probe capable of delivering more precise treatment to women with gynecological cancers, reported authors of a feasibility study published in the Journal of Medical Imaging.

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ACR launches new AI software platform, announces partnership with GE

The American College of Radiology (ACR) Data Science Institute (DSI) has launched the ACR AI-LAB, a free software platform that will help radiologists collaborate to create, validate and use AI. The college also announced it is partnering with GE Healthcare on the ACR AI-LAB.

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OCT angiography shows promise for diagnosing Alzheimer’s

Clinicians can use optical coherence tomography angiography (OCTA) to noninvasively diagnose patients with early cognitive impairment, an early indicator of Alzheimer’s disease (AD), reported authors of a single-center study published in PLOS One.

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4 challenges machine learning must overcome to help clinicians

Machine learning has the potential to reshape the patient-doctor relationship, according to a new review published in the New England Journal of Medicine, but it must overcome a few challenges first.

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Deep learning model only needs a single breast MR image to assess cancer risk

A new AI model can accurately determine a patient’s five-year cancer risk based on a single breast MR image, outperforming state-of-the art risk assessment models.

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Deep learning bests radiologists at classifying thoracic disease on chest x-rays

The algorithm was externally validated on 486 normal chest radiographs and 529 abnormal chest radiographs taken from four different institutions across multiple continents.

FDA working on new steps for regulating AI devices

The FDA announced Tuesday, April 3, that it is working on a new framework to regulate AI-based medical devices that continually learn from healthcare data.

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Positron partners with Upbeat Cardiology Solutions to improve cardiac PET/CT access

Positron, a New York-based nuclear imaging company, will now provide Upbeat Cardiology Solutions with advanced PET/CT systems and services. 

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‘A huge win’: CMS significantly increases Medicare payments for cardiac CT

CMS has more than doubled the CCTA payment rate from $175 to $357.13. The move, expected to have a significant impact on the utilization of cardiac CT, received immediate praise from imaging specialists.