Advanced visualization software developer Ziosoft of Redwood City, CA, is partnering with Medicsight to market the London-based company's computer-aided detection (CAD) software integrated within the Ziostation thin-client 3D system.
The combined CT colonography product is expected to launch early next year, following regulatory clearance in the U.S.
The proof-of-concept integration will be demonstrated at Ziosoft's booth during next week's RSNA meeting.
Related Reading
Ziosoft expands office space, November 18, 2008
Road to RSNA, Advanced Visualization, Ziosoft, November 6, 2008
Ziosoft to partner with Johns Hopkins, June 16, 2008
Medicsight submits 510(k) for ColonCAD, November 20, 2008
Road to RSNA, CAD, Medicsight, October 30, 2008
Medicsight touts ESGAR colon CAD data, June 19, 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)
