This channel includes news and technology innovations for artificial intelligence (AI) software, also referred to as deep learning, cognitive computing and machine learning. AI technology is being integrated in radiology for imaging appropriate use criteria (AUC), clinical decision support, predictive analytics and to assist radiologists with improved workflow.
Figure 1: Examples of chest CT images of COVID-19 (+) patients and visualization of features correlated to COVID-19 positivity. For each pair of images, the left image is a CT image showing the segmented lung used as input for the CNN (convolutional neural network algorithm) model trained on CT images only, and the right image shows the heatmap of pixels that the CNN model classified as having SARS-CoV-2 infection (red indicates higher probability). (a) A 51-year-old female with fever and history of exposure to SARS-CoV-2. The CNN model identified abnormal features in the right lower lobe (white color), whereas the two radiologists labeled this CT as negative. (b) A 52-year-old female who had a history of exposure to SARS-CoV-2 and presented with fever and productive cough. Bilateral peripheral ground-glass opacities (arrows) were labeled by the radiologists, and the CNN model predicted positivity based on features in matching areas. (c) A 72-year-old female with exposure history to the animal market in Wuhan presented with fever and productive cough. The segmented CT image shows ground-glass opacity in the anterior aspect of the right lung (arrow), whereas the CNN model labeled this CT as negative. (d) A 59-year-old female with cough and exposure history. The segmented CT image shows no evidence of pneumonia, and the CNN model also labeled this CT as negative.
A complex multicompartmental cerebral hemorrhage on a single axial CT image displayed using the annotation tool in a single portal window. Hemorrhage labels (left column) relevant to the image display on the bottom of the image once selected. ASNR = American Society of Neuroradiology RSNA = Radiological Society of North America. Image courtesy of RSNA
U.S. Army Spc. Jonathon Hyde and Spc. Casymn Harrison from the 1434th Engineer Company, Grayling, Mich., Michigan National Guard, prepare patient rooms at TCF Regional Care Center in Detroit in advance of receiving COVID-19 patients, April 9, 2020. The TCF Center in Detroit has been converted into a 970-bed alternative care facility for COVID-19 patients by the Federal Emergency Management Agency, in partnership with the U.S. Army Corps of Engineers and Michigan National Guard. (Photo courtesy of U.S. Air National Guard photo by Master Sgt. Scott Thompson)
Table 1. Compared to 2-D mammography, which yields four images per patient, digital breast tomosynthesis (DBT), or 3-D mammography, produces hundreds of images per patient. While this provides more information for clinicians, the exponential increase in data can result in reader fatigue and burnout, which may ultimately affect patient care.
Varian received FDA clearance for its Ethos therapy in February 2020, shown here displayed for the first time at ASTRO 2019. It is an adaptive intelligence solution that uses onboard AI in the treatment system to take the cone beam CT imaging on the system, compare it to the treatment plan and deliver an entire adaptive treatment plan in a typical 15-minute treatment time slot, from patient setup through treatment delivery.