Contributions from new acquisition Dade Behring helped Siemens Healthcare to a 10% revenue gain in its fiscal third quarter, although unadjusted revenue and profit slipped in its imaging division.
For the period (end-June 30), the Erlangen, Germany-based vendor had revenues of 2.677 billion euros ($4.21 billion U.S), up from 2.431 billion euros ($3.83 billion U.S.) a year ago. Siemens had a profit of 326 million euros ($513.2 million U.S.), up from 307 million euros ($483.3 million U.S.) in the third quarter of 2007.
Siemens noted that growth was more modest in established markets characterized by slower economic growth, tightening credit, and by U.S. public policy affecting medical imaging.
Siemens' Imaging and IT division produced revenues of 1.569 billion euros ($2.47 billion U.S.), up 3% on an organic basis but down 4% on an unadjusted basis from the 1.639 billion euros ($2.58 billion U.S.) turned in last year. Hurt by substantial currency effects, profit slipped from 223 million euros ($351 million U.S.) to 199 million euros ($313.3 million U.S.), Siemens said.
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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&dpr=2&fit=crop&h=167&q=70&w=250)
