Women's imaging vendor Hologic plans to feature its 3D mammography system at this week's Arab Health meeting in Dubai, United Arab Emirates.
Hologic is highlighting its Selenia Dimensions 3D mammography system with C-View software, which allows a 2D image to be constructed from a 3D dataset without the need for a separate 2D x-ray exposure, Hologic said. The company is also featuring its Affirm 3D mammography biopsy tool, which helps users localize and target breast lesions. Affirm can be used with Hologic's Eviva and Atec vacuum-assisted breast biopsy devices.
Finally, Hologic is highlighting Selenia Dimensions Avia, a lower-cost option for those seeking a 2D screening-only system or a screening and diagnostic system with the possibility of a future upgrade to 3D mammography, Hologic said.
![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)
