COLIPE Software for Researchers

Sample COLIPE Output

Sample COLIPE Output

 

COLIPE offers an ideal, fully automated solution for non-commercial researchers to quickly and efficiently segment and analyze large quantities of knee MRI image data.

Qmetrics Technologies has a long, proud history of working with academic researchers on the forefront of MSK studies. The company has offered various advanced medical imaging products to support academic researchers, whether they are applying for a grant or conducting a grant funded study. Recently, Qmetrics launched COLIPE, the latest in a line of medical imaging software technologies developed to aid non-commercial MSK research worldwide.

COLIPE – Command Line Image Processing Executable

COLIPE is a software command-line executable for Window that segments fat-suppressed knee MRI images using a fully automated, atlas based methodology.¹ It saves valuable time, while providing improved segmentation precision and repeatability in the researchers’ own laboratory setting.

COLIPE Functions Include:

  • Segments knee MR images into bones and cartilage and defines the tissue.
  • Quantifies pre-set parameters of the segmented structures.
  • 3D models are generated from segmented structures.

COLIPE generates DICOM output, suitable for use with a lab’s existing analysis software tools, including:

  • DICOM images with segmented tissues labeled.
  • DICOM images with quantification data encoded in the DICOM header tags.
  • .x3d files of surface rendered structures.
  • .xml file containing measurements of segmented structures.

Qmetrics licenses COLIPE on an annual basis for unlimited use on one platform. The software can be used only for academic, non-commercial use and includes:

  • COLIPE executable (Windows²)
  • Image viewer/editor
  • Knee atlas set
  • Documentation
  • Programming examples

With COLIPE, MSK researchers have access to precise, efficient & repeatable Knee MRI Segmentation and Analysis Tools in their own lab.

 

To download a COLIPE brochure, click here.

 

For more information about COLIPE, contact us.

 

1: Tamez-Peña JG, Farber J, González PC, Schreyer E, Schneider E, Totterman S. Unsupervised segmentation and quantification of anatomical knee features: data from the Osteoarthritis Initiative. IEEE Trans Biomed Eng. 2012 Apr;59(4):1177-86. doi: 10.1109/TBME.2012.2186612. Epub 2012 Feb 3. PubMed PMID: 22318477.
2: Linus & OS/X are planned.