Swedish firm SharpView of Linköping, Sweden, a partner of ContextVision, has received welcome clinical results from Massachusetts General Hospital in Boston that suggest its image-enhancing software helps reduce CT radiation dose.
The results, presented at the American Roentgen Ray Society (ARRS) meeting in Boston, show a relative dose reduction of as much as 75% for kidney assessment and at least 50% for abdominal exams when SharpView's software package is used, the company said.
The technology is based on algorithms that filter out noise, making imaging with lower radiation amounts possible.
Related Reading
ContextVision installs low-dose CT systems, November 9, 2006
ContextVision lands Swedish grant, September 19, 2006
ContextVision licenses GOPView, July 14, 2006
ContextVision hits milestone, June 14, 2006
ContextVision reports Q1 OEM growth, April 11, 2006
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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)
