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The Benefits of Integrated RIS/PACS
at Blue Ridge HealthCare Presented by Siemens Medical Solutions Siemens Medical Solutions invites you to learn how Blue Ridge HealthCare has used the Siemens Cosmos integrated RIS/PACS system to help it:
Additional benefits realized from the Cosmos RIS/PACS installation include an improved workflow that reduced the number of steps in the imaging process by nearly 50%, as well as a complete filmless and paperless environment achieved in the ED, by using interactive documents. |
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What is Blue Ridge HealthCare? Blue Ridge HealthCare consists of two hospitals that are both affiliated with the Carolinas Medical Center.
Blue Ridge personnel who will share their insights and experiences include:
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Glimpse the Future
This symposium will also look to the near future, when this solution will be expanded to the Valdese Hospital and the Outpatient Imaging Center after a $100 million renovation and expansion project is completed. At that time, integrated voice recognition will be deployed and an enterprise-wide filmless and paperless environment will be created. | |
The Benefits of Integrated RIS/PACS at Blue Ridge HealthCare Presented by Siemens Medical Solutions
May 23, 2005
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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.auntminnie.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)
