HiwiBoneSegm

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

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Robust bone segmentation in CT images

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Figure 1: Skeleton extracted from a CT image.

Project Description

Bone segmentation in CT images of healthy young subjects acquired with the same protocol is a relatively easy problem. However, different pathologies, in particular age-related, make it more difficult. We want to develop a robust method for these more difficult cases.

Requirements

  • Good Programming Skills (Python and/or C++)
  • Ability to work independently
  • Experience with medical images processing is not required

Contact

If you are interested in the project or if you have any questions please contact


ProjectForm
Title: Robust bone segmentation in CT
Abstract: We are looking for a motivated student to develop a bone segmentation approach in CT images. The method will have to be robust enough to cope with different pathologies (arthrosis, calcifications, ...). The student should have good programming skills in python and/or C++. Medical imaging experience is not required.
Student:  
Director: Prof. Dr. Bjoern Menze
Supervisor: Marie Bieth
Type: Hiwi
Area: Segmentation, Medical Imaging
Status: finished
Start:  
Finish:  
Thesis (optional):  
Picture:  


Edit | Attach | Refresh | Diffs | More | Revision r1.2 - 14 Jul 2016 - 11:04 - MarieBieth