Technology

Five artificial intelligence (AI) algorithms for mammography assessment were better at predicting breast cancer risk over five years than the Breast Cancer Surveillance Consortium (BCSC) risk model, according to new retrospective research involving over 13,000 women.

Powered by deep learning technology, Sonic DL reportedly facilitates the acquisition of cardiac magnetic resonance imaging (MRI) scans at 12 times the speed of conventional MRI systems.

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The artificial intelligence (AI)-powered Ezra Flash reportedly enhances magnetic resonance imaging (MRI) and enables significant reductions in scan times and costs for full-body MRI.

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Precision DL, a deep learning-based software which will be available on GE HealthCare’s Omni Legend PET/CT device, reportedly increases the detectability of small, low-contrast lesions by 42 percent.

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Emerging breast ultrasound research showed the use of computer-aided diagnosis (CAD), powered by deep learning, led to 24 percent and 36.9 percent improvements in accuracy and specificity, respectively, in the use of BI-RADS classifications by radiologists without breast ultrasound expertise.

Six reader studies on digital mammography revealed a pooled sensitivity rate of 80.8 percent for stand-alone artificial intelligence (AI) in comparison to 72.4 percent for radiologist assessment while seven historic cohort studies showed a 75.8 percent pooled sensitivity rate for stand-alone AI versus 72.6 percent for radiologist interpretation of digital mammography.

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Through artificial intelligence (AI), Neurophet AQUA reportedly provides segmentation and analysis of brain magnetic resonance imaging (MRI) for possible brain atrophy in five minutes.

The artificial intelligence (AI)-enabled CT 3500 system reportedly reduces patient positioning time by 23 percent, improves low-contrast detectability by 60 percent and facilitates up to an 80 percent reduction in radiation dosing.

Updates to Contour ProtegeAI 4.0 reportedly include enhanced algorithms for radiation oncology segmentation and molecular radiotherapy.

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The DRX-Rise Mobile X-ray System reportedly combines optimal image quality with enhanced maneuverability and ease of use for radiologists.

Adjunctive use of an artificial intelligence (AI) software demonstrated nearly equivalent sensitivity and over 28 percent higher accuracy in comparison to radiologist assessment of breast ultrasound images for breast lesions, according to new research presented at the recent Society of Breast Imaging (SBI) conference.

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In a review of the literature, this author discusses the viability of artificial intelligence (AI), parallel imaging, compressed sensing and simultaneous multi-slice excitation for improving the scan times and use of magnetic resonance imaging (MRI) to facilitate CyberKnife treatment.

Regardless of experience level, radiologists are likely to be affected by automation bias when utilizing adjunctive artificial intelligence (AI) for mammography interpretation, according to newly published research.

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The artificial intelligence (AI)-powered Neuro Suite reportedly enables radiologists to access leading neurological AI algorithm solutions in the field, including the brain magnetic resonance imaging (MRI) segmentation capabilities of the Combinostics’ algorithm that can help differentiate degenerative pathologies such as Alzheimer’s disease and dementia.

The artificial intelligence (AI)-powered EchoGo Amyloidosis can reportedly detect cardiac amyloidosis by assessing a single echocardiogram.

Catch up on the top AI-related news and research from the past month.

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An emerging artificial intelligence (AI) software reportedly detected liver metastases in 53.7 percent of cases involving missed findings by radiologists.

In a new study involving over 11,700 chest computed tomography (CT) scans in oncology patients, adjunctive artificial intelligence software demonstrated a sensitivity rate of 91.6 percent for incidental pulmonary embolism (IPE) and reduced median detection and notification time for IPE-positive scans from multiple days to one hour for a radiology department at a comprehensive cancer center.

Powered by artificial intelligence (AI), the Rapid NCCT Stroke modality is reportedly the first medical device to gain FDA 510(k) clearance for detecting suspected large vessel occlusion and intracranial hemorrhage based on assessment of non-contrast computed tomography (NCCT).

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The artificial intelligence (AI) triage and notification indications include acute subdural/epidural hematoma and acute subarachnoid hemorrhage for head computed tomography (CT) imaging.