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.
The Food and Drug Administration (FDA) has granted 510(k) clearance for Precision DL (GE HealthCare), an artificial intelligence (AI)-enabled image processing software, which may offer significant improvements in contrast-to-noise ratio (CNR), the accuracy of feature quantification, and the diagnosis of small lesions on positron emission tomography (PET)/ computed tomography (CT).
Engineered with a deep neural network trained on thousands of images via multiple reconstruction methods, Precision DL will be accessible through the Omni Legend PET/CT device (GE HealthCare).
The company said Precision DL offers a variety of imaging enhancement benefits including:
• an average 42 percent increase in the detection of small, low-contrast lesions;
• an average 23 percent improvement in CNR; and
• a 14 percent improvement in the accuracy of feature quantification.
“Precision DL enhances image quality – enabling us to spot small lesions, including on images obtained with very low dose injections and short bedtimes, to potentially start treatment and monitoring early, which might result in improved outcomes,” noted Flavio Forrer, M.D., Ph.D., the chairman of nuclear medicine at Kantonsspital St. Gallen in Switzerland.
(Editor’s note: For related content, see “GE Healthcare Launches Omni Legend PET/CT System at EANM Congress.”)
MRI-Based Deep Learning Algorithm Shows Comparable Detection of csPCa to Radiologists
May 8th 2024In a study involving over 1,000 visible prostate lesions on biparametric MRI, a deep learning algorithm detected 96 percent of clinically significant prostate cancer (csPCa) in comparison to a 98 percent detection rate for an expert genitourinary radiologist.
Study Finds High Concordance Between AI and Radiologists for Cervical Spine Fractures on CT
May 6th 2024Researchers found a 98.3 percent concordance between attending radiology reports and AI assessments for possible cervical spine fractures on CT, according to new research presented at the 2024 ARRS Annual Meeting.
Can a CT-Based Radiomics Model Bolster Detection of Malignant Thyroid Nodules?
May 3rd 2024A computed tomography (CT)-based radiomics model that includes 28 radiomic features showed significantly higher accuracy, sensitivity, and specificity than conventional CT in differentiating benign and malignant thyroid nodules, according to newly published research.
New Literature Review Finds ChatGPT Effective in Radiology in 84 Percent of Studies
April 29th 2024While noting a variety of pitfalls with the chatbot ranging from hallucinations to improper citations, the review authors found the use of ChatGPT in radiology demonstrated “high performance” in 37 out of 44 studies.