Ricardo Khine, PhD, has been appointed a professor at Buckinghamshire New University in the U.K.
Ricardo Khine, PhD.A therapeutic radiographer, Khine was recognized for his significant contribution to professional practice and education, according to the university. He has spent more than 22 years in therapeutic radiography, including 13 years in higher education as a senior academic, and he has also worked in the U.S. and Australia.
Khine now serves as the head of the School of Health and Social Care Professions at Buckinghamshire New University.
Khine has promoted the therapeutic radiographer profession in activities for the U.K. Society of Radiographers (SoR), the European Federation of Radiographer Societies, and Health Education England. Furthermore, he is also a senior fellow of the Higher Education Academy and a member of the Academy of Medical Educators.
Khine received his doctorate in 2017 for research on the perceived impact of the consultant therapeutic radiographer role in clinical practice, the university said. His current research involves advanced clinical practitioner roles in therapeutic radiography.
![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)
