GE Healthcare has been chosen by the Medical Imaging Antilles-Guyane purchasing group in France to lead a consortium that will develop cloud imaging platforms between physicians in Martinique, Guadeloupe, and French Guyana.
The platform will allow physicians across these three regions to share patient images. The initiative is financed by France's Ministry of Health (Agences Regionales de Santé), and will also include GE's vendor neutral archive, its PACS with universal viewer, and its desktop RIS, according to GE. The contract is for up to 12 years.
The program will start at nine pilot sites within the next six months, including hospitals in Martinique, Guadeloupe, Cayenne, Basse-Terre, and West-Guyanese; two private imaging centers in Martinique, a private radiology center in Saint Martin, and the Medical Surgery Center in Kourou, French Guyana, GE said.
![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)
