High order bookings propelled Swedish PACS vendor and digital mammography developer Sectra of Linköping to greater revenues and profits in fiscal 2008.
For the year (end-March 31), net sales increased 10% to $124 million (U.S.), compared with $112.5 million in fiscal 2007. The company's profit climbed 14% to $13.3 million for the 12-month period, compared with $11.7 million in the previous year.
Sectra's order bookings rose 48% to $169 million during fiscal 2008, compared with $114 million for 2007. International expansion continued, with markets outside Sweden now accounting for 67% of Sectra's sales. The company's area of greatest growth is in the U.S. market.
Fourth-quarter net sales rose 9% to $37.5 million, compared with $34.2 million in the fourth quarter of 2007. Profit totaled $7 million, compared with $3.9 million in the previous fourth quarter.
Related Reading
Sectra adds FFDM customer, May 6, 2008
Sectra adds Japanese distributor, April 2, 2008
Sectra installs new version of PACS software, March 10, 2008
Sectra sales climb in Q3, March 4, 2008
Sectra wins PACS deal for London hospitals, January 3, 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)
