C-arm developer Ziehm Imaging of Nuremberg, Germany, has rolled out a new surgical C-arm system in Europe.
Ziehm Vision RFD features a 30 x 30-cm flat-panel digital detector for an expanded field-of-view for interventional radiology, neurosurgery, vascular surgery, and cardiology applications.
Ziehm Vision RFD's 1.5K x 1.5K high-resolution detector and an expanded range of more than 16,000 grayscale shades enable better visualization of fine details in vascular and bony anatomy, according to the company.
Related Reading
Road to RSNA, Digital X-Ray, Ziehm Imaging, October 22, 2008
Ziehm, BrainLab partner, October 21, 2008
Ziehm debuts digital C-arms at RSNA, November 27, 2007
Road to RSNA, Digital X-Ray, Ziehm Imaging, October 23, 2007
Ziehm's IGS system to enter the U.K., June 28, 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)
