Philip Ward, Erik Ridley, Wayne Forrest, and Rebekah MoanISTop 5 trends from ECR 2018 in ViennaThe huge red dragon that dominated the registration area of ECR 2018 looked amazing in everybody's photos, but what were the lasting impressions and meaningful issues to take away from this year's congress in a decidedly chilly Vienna? Our editorial team has put together a list of the five key themes.March 7, 2018Page 1 of 1Top StoriesAIImaging fellow tries vibe coding to solve radiology challengesVibe coding outside the radiology department led to exploring real-world use cases.ISMRM 2026ISMRM annual meeting in Cape Town to highlight South African 'Ubuntu'InterventionalRadiation segmentectomy can be optimized before liver transplantWomens ImagingCardiac devices affect mammography image qualitySponsor ContentTurning Innovation into Everyday Efficiency
![Overview of the study design. (A) The fully automated deep learning framework was developed to estimate body composition (BC) (defined as subcutaneous adipose tissue [SAT] in liters; visceral adipose tissue [VAT] in liters; skeletal muscle [SM] in liters; SM fat fraction [SMFF] as a percentage; and intramuscular adipose tissue [IMAT] in deciliters) from MRI. The fully automated framework comprised one model (model 1) to quantify different BC measures (SAT, VAT, SM, SMFF, and IMAT) as three-dimensional (3D) measures from whole-body MRI scans. The second model (model 2) was trained to identify standardized anatomic landmarks along the craniocaudal body axis (z coordinate field), which allowed for subdividing the whole-body measures into different subregions typically examined on clinical routine MRI scans (chest, abdomen, and pelvis). (B) BC was quantified from whole-body MRI in over 66,000 individuals from two large population-based cohort studies, the UK Biobank (UKB) (36,317 individuals) and the German National Cohort (NAKO) (30,291 individuals). Bar graphs show age distribution by sex and cohort. BMI = body mass index. (C) After the performance assessment of the fully automated framework, the change in BC measures, distributions, and profiles across age decades were investigated. Age-, sex-, and height-adjusted body composition reference curves were calculated and made publicly available in a web-based z-score calculator (https://circ-ml.github.io).](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/05/body-comp.XgAjTfPj1W.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
