Sales from recent acquisitions helped the healthcare division of German industrial conglomerate Siemens AG kick off fiscal-year 2008 with increases in both revenues and profit in its first fiscal quarter (end-December 31).
Revenues at Siemens Medical Solutions increased to $2.65 billion euros ($3.86 billion U.S.), up 26% compared with $2.1 billion euros ($3.06 billion) in the first quarter of fiscal year 2007. The division's profit rose to $332 million euros ($484 million), a gain of 9% over $304 million euros ($443.8 million) in the same quarter of fiscal-year 2007.
New orders also advanced in the first quarter to $2.8 billion euros ($4.08 billion), compared with 2.21 billion euros ($3.22 billion) in the same quarter last year.
Parent company Siemens AG credited the rise in first-quarter results to its healthcare division's ability to more than offset the effect of negative currency trends and a weaker U.S. market through new volume from acquisitions.
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London hospital to install Siemens' 3-tesla MRI unit, January 10, 2008
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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)
