DeJarnette Research Systems of Towson, MD, has completed the first installation of its dyseCT CT workflow engine in Europe.
The unit was installed in December at St. Bartholomew's and the London NHS Trust at the Royal London Hospital in the U.K.
DeJarnette's dyseCT is designed to identify multiple procedure studies, and modifies the DICOM modality worklist using a group procedure to replace the multiple procedures. It also analyzes CT images and automatically associates them with a specific anatomical region without manual intervention, according to the company.
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DeJarnette readies dyseCT VMS, December 13, 2007
DeJarnette reaches migration milestone, September 6, 2007
DeJarnette to open London office, April 11, 2007
DeJarnette releases dyseCT 3.0, February 14, 2007
DeJarnette posts double-digit sales growth, promotes Finegan, February 8, 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&dpr=2&fit=crop&h=167&q=70&w=250)
