MaBaIDPInterventionalToolTracking

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

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Detection of interventional tools in moving images

Project type: klinisches Anwendungsprojekt (im Bachelor oder Master-Nebenfach Medizin) / Bachelorarbeit / Masterarbeit
Advisor: Nassir Navab
Supervision by: Dr. Diana Mateus, Dr. Stefanie Demirci


Figure 1: Detection and visualisation of a catheter in an image guided neurological intervention

Project Description

Fluoroscopic images are used in intravascular guided interventions to help physicians steer the tools towards a desired location. The goal of this project is to use state of the art image processing and modelling techniques in order to separate the background from the tools, thereby improving their visualisation for easier guidance. The challenges we want to address are both the low signal to noise ratio as well as the deformations caused by motion, e.g. respiratory and/or cardiac.

The difficulty of the project will be adapted to an IDP, Bachelor or Master Thesis.

Tasks

  1. Detection and visualisation for static videos.
  2. Detection and visualisation for videos with larger image deformations.
  3. Quantitative Validation

Requirements

  • Good programming skills in MATLAB
  • Programming skills in C++ are a plus.
  • Basic knowledge of image processing is a plus.

Contact

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

References


ProjectForm
Title: Detection of interventional tools in moving images
Abstract: Fluoroscopic images are used in intravascular guided interventions to help physicians steer the tools towards a desired location. The goal of this project is to use state of the art image processing and modelling techniques in order to separate the background from the tools, thereby improving their visualisation for easier guidance. The challenges we want to address are both the low signal to noise ratio as well as the deformations caused by motion, e.g. respiratory and/or cardiac.
Student:  
Director: Prof. Dr. Nassir Navab
Supervisor: Dr. Diana Mateus, Dr. Stefanie Demirci
Type: DA/MA/BA
Area: Registration / Visualization, Machine Learning, Medical Imaging, Computer Vision
Status: finished
Start:  
Finish:  
Thesis (optional):  
Picture:  


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