The German Radiological Society (Deutsche Röntgengesellschaft, DRG) will hold a workshop on 1-2 April at Gastwerk Hamburg with the aim of increasing networking and boosting the influence of women in radiology.
The workshop is being spearheaded by Dr. Kerstin Westphalen, president of the 103rd German X-ray Congress. She stated a goal last year was to ensure at least 35% of speakers are women in the German Radiology Congress (Deutscher Röntgenkongress, RöKo) training program. The DRG launched a mentoring program to foster more female speakers.
The upcoming workshop will expand attendees' view of career opportunities in radiology and communication in everyday working life. Attendees will have the chance to benefit from the tips and tricks of experienced coaches and visualize their strengths in intensive group training sessions.
An official agenda with a detailed program and schedule is available. The cost for the workshop is 120 euros, excluding accommodation.
More information is available on the DRG website.
![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.auntminnieeurope.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)
