Sales growth in its Imaging IT Solutions unit propelled PACS firm Sectra to a 20.9% increase in net sales for the first six months of its 2014/2015 fiscal year.
For the period (end-October 31), Sectra had net sales of 451.5 million Swedish kronor (48.4 million euros), compared with 373.6 million kronor (40.1 million euros) in the first six months of 2013/2014. The company had profit before tax of 81.1 million kronor (8.7 million euros), compared with 47.2 million kronor (5.1 million euros) in the same period a year ago.
Sectra's Imaging IT Solutions business generated 409.5 million kronor (43.9 million euros) in sales, up 14.8% from the 356.8 million kronor (38.3 million euros) reported in the first half of 2013/2014. Operations in the U.K. and the U.S. generated the largest sales growth, according to the vendor.
The unit had operating profit of 75.6 million kronor (8.1 million euros) in the first six months of 2014/2015, compared with 63.7 million kronor (6.8 million euros) in the same period a year ago.
![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)
