Biomedical image processing

Information processing is now one of the main frontiers in medical imaging. Modern medical imaging modalities revolutionize many aspect of the practice of medicine. Whereas radiology was previously associated with diagnostic only-application, interventional tools are emerging, thanks to more accurate, more manageable technologies. Advanced methodologies, such as computational anatomy and image-guided procedures, are now reality. They promise a better understanding of the human body and better, less invasive treatments. Those benefits come, however, with a huge increase in numerical data volume.

In today's context, where qualified workmanship is scarce and expensive, the automated processing of medical images is becoming increasingly relevant. Software tools have potentials in assisting practitioners in data interpretation, therefor lowering human-induced bias, reducing cost and even enabling new applications.

Synchromedia is active in the development of medical image processing methods in the following fields of applications:

  • 3D/2D registration
  • Segmentation of 3D vascular structure in CTA volumes
  • Segmentation of brain tissues in MRI volumes
  • De-noising and enhancement filters for application in orthopedics

Read the articles below for a more in-depth overview of our works.

Articles in this category


A [too] short introdution to level set segmentation

The level set method, introduced by Osher and Sethian, is a generic framework for curve evolution in N dimensions. Within this framework, a N-D curve is represented by a (N + 1)-D surface, as shown on the following picture:

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