The U.K. Royal College of Radiologists (RCR) is inviting members and fellows of its clinical radiology faculty to apply for a professorship funded by the publishers of Clinical Radiology.
The Roentgen Professorship is open to clinical radiologists who hold either a National Health Service (NHS) consultant post or an academic radiology appointment below the grade of professor in the U.K. In spring of 2015, the Roentgen Professor will visit at least five U.K. training sites to encourage research in clinical radiology, giving tutorials and a lecture during each visit. Funding of up to 3,000 pounds (3,612 euros) will be available to cover the appointee's costs, the RCR said.
As well, the Roentgen Professor may be asked to provide advice and guidance on research issues to the publishers of Clinical Radiology, which could involve attendance at up to two meetings during 2015.
Applications should include a full curriculum vitae, a description of the applicant's research record, and a description of why the applicant would be suitable for appointment to the post. Applications should be sent by email only to Cilla Heath, RCR's education administrator, no later than 11 April.













![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&fit=crop&h=112&q=70&w=112)




