The British Institute of Radiology (BIR), together with GE HealthCare, has issued a final call for submissions for their 2023 Radiation Safety Travel Award.
The award is made every two years. The closing date for applications is 31 May 2023. Winners receive up to 1,000 pounds (1,150 euros) for travel to their chosen scientific conference to present their presentation/poster, according to the announcement.
Applicants must design a new resource or tool to improve radiation safety in healthcare. This may be innovative software or a novel use of new technologies. In addition, following the presentation of their work, the winner must submit their research to a relevant British Journal of Radiology journal for consideration for publication, as well as submit a written report to the BIR on their experience at the relevant conference, according to the guidelines.
Only BIR members are eligible to apply. Interested parties are encouraged to complete the application form and return by the deadline to Lucy Stewart at [email protected]
![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)
