Healthcare IT and advanced visualization developer Merge Healthcare of Milwaukee has released its latest update to Cedara I-ReadMammo for digital breast imaging review.
Cedara I-ReadMammo 6.5 supports 10-bit medical monitors, which display up to 1,024 simultaneous levels of gray, compared with 256 levels on 8-bit monitors, and features workflow enhancements in functions, such as lesion contouring and image cross correlation.
Cedara I-ReadMammo is available in both standalone and plug-in versions to incorporate into a PACS viewer or to interface with existing technologies.
Related Reading
Merge upgrades eFilm Workstation, March 3, 2009
Merge unveils new ortho software version, February 25, 2009
Merge posts Q4 profit, February 12, 2009
Merge names China staff, January 23, 2009
Merge reacquires China unit, January 7, 2009
Copyright © 2009 AuntMinnie.com
![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)
