Morris Panner[email protected]Cardiac ImagingIntegrated cardiac workflow, imaging tools transform access/demand equationInteleradIn a new column, Morris Panner of Intelerad Medical Systems discusses challenges and opportunities in cardiac imaging.November 17, 2025AIAI education is a necessity for newest class of radiologistsInteleradIntelerad President Morris Panner emphasizes the importance of education on radiology AI technology for new radiologists.August 2, 2024AIEmbracing and accelerating AI in healthcareArtificial intelligence (AI) is being woven into the fabric of our everyday lives. Yet for some, AI still generates some concern. Industry expert Morris Panner discusses some of the incredible benefits to the use of AI, particularly in healthcare.July 26, 2022IS5 healthcare trends to watch in 2016In 2015, we heard time and time again that the healthcare landscape was changing rapidly as we moved from a fee-for-service world to a risk-based/value-based world. In this article, DICOM Grid CEO Morris Panner discusses how some of the major emerging trends in healthcare will affect healthcare IT in 2016.February 1, 2016IS5 tips to drive adoption of patient portals in radiologyThe establishment of patient portals has blurred the lines of what is considered to be appropriate doctor-patient communication outside of the medical office. Patients may be wary of portals, but DICOM Grid CEO Morris Panner shares five tips for allaying their concerns and driving higher adoption.August 10, 2015Page 1 of 1Top StoriesCTPhoton-counting CT: The art of transitionIn a new column, Matthew Dedman of Siemens Healthineers North America discusses the benefits and challenges of transitioning to photo-counting CT.UltrasoundSuspended suits offer protection for interventional echocardiographersCTGoogle AI Studio shows potential for AI-based lung cancer detectionRisk ManagementPodcast: Whose duty is it to ensure MRI safety?Sponsor ContentModernizing Radiotherapy Workflows
![Images show the pectoralis muscles of a healthy male individual who never smoked (age, 66 years; height, 178 cm; body mass index [BMI, calculated as weight in kilograms divided by height in meters squared], 28.4; number of cigarette pack-years, 0; forced expiratory volume in 1 second [FEV1], 97.6% predicted; FEV1: forced vital capacity [FVC] ratio, 0.71; pectoralis muscle area [PMA], 59.4 cm2; pectoralis muscle volume [PMV], 764 cm3) and a male individual with a smoking history and chronic obstructive pulmonary disorder (COPD) (age, 66 years; height, 178 cm; BMI, 27.5; number of cigarette pack-years, 43.2, FEV1, 48% predicted; FEV1:FVC, 0.56; PMA, 35 cm2; PMV, 480.8 cm3) from the Canadian Cohort Obstructive Lung Disease (i.e., CanCOLD) study. The CT image is shown in the axial plane. The PMV is automatically extracted using the developed deep learning model and overlayed onto the lungs for visual clarity.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/03/genkin.25LqljVF0y.jpg?auto=format%2Ccompress&crop=focalpoint&dpr=2&fit=crop&h=167&q=70&w=250)