Philips Healthcare of Andover, MA, has signed a deal to buy Tomcat Systems, a developer of cardiovascular information systems software based in Belfast, Northern Ireland.
Tomcat's software enables users to collect and aggregate data relative to the cardiac care of patients by connecting with different clinical information systems, such as cath lab workflow management systems and PACS networks. The firm's software also provides scheduling, staff and resource management, cost capturing, and the generation of reports and statistical information.
Philips said Tomcat's software is a good match for the company's current cardiology information system (CIS), and the vendor is working to introduce an integrated CIS in North America and other markets. Tomcat has about 25 employees.
Related Reading
Philips inks Chinese DR contract, March 20, 2008
Philips debuts wireless tracking system, March 10, 2008
Philips debuts HD7 ultrasound system, March 7, 2008
Philips adds to health informatics division, February 25, 2008
Philips completes Visicu purchase, February 21, 2008
Copyright © 2008 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)
