Canadian PACS vendor RamSoft said that nonprofit organization Teleradiology Without Borders is utilizing its PACS network to provide imaging services to several underdeveloped countries.
The Luxembourg-based volunteer organization seeks to provide reading services for imaging studies from Cameroon, Afghanistan, Burkina Faso, and the Democratic Republic of the Congo, according to RamSoft of Toronto.
Related Reading
RamSoft to roll out PowerServer RIS/PACS, May 13, 2008
RamSoft to unveil new PACS, February 15, 2008
StructuRad teams with Infinitt, RamSoft to launch MacroLive, November 26, 2007
Aris to use RamSoft technology, November 13, 2007
Road to RSNA, PACS Accessories, RamSoft, October 30, 2007
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![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)




