Breast imaging developer Dexela has begun commercial shipments of its DexTop breast imaging workstation.
DexTop supports full-field digital mammography (FFDM) images as well as breast tomosynthesis, according to the London-based firm. It employs a 64-bit computing platform and graphics hardware and a modular, Web services-based architecture, Dexela said. DexTop has received both the European CE Mark and U.S. Food and Drug Administration (FDA) 510(k) clearance.
In other Dexela news, the company has named Peter Denyer as director and nonexecutive chairman. Denyer founded and built CMOS imager chip developer Vision Group and will replace Mike Brady as chairman. Brady will remain on the board and continue to serve as chairman of Dexela's scientific advisory board, Dexela said.
Dexela also said it has raised 2.6 million pounds ($5.2 million U.S.) through a round of fundraising, which included Close Ventures and London Technology Fund as main investors. Proceeds will be used to support ongoing development and commercialization of Dexela's imaging technology, according to the company.
Related Reading
Dexela awarded development grant, November 28, 2007
British firm Dexela focuses on 3D mammography workstation, October 27, 2006
Dexela scores funding, May 19, 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)
