IdpDeviceDetection

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

Stent Detection in X-ray Images

Project type: klinisches Anwendungsprojekt (im Bachelor-Nebenfach Medizin)
Advisor: Nassir Navab
Supervision by: Stefanie Demirci

Abstract

Most catheterization procedures are performed under constant 2D X-ray imaging. Image-guided intervention (IGI) solutions aim at enhancing this 2D information by integrating the preoperatively acquired 3D patient scan into the intervention room. This is usually done by 2D-3D registration algorithms that require appearance of both images to be similar. Dissimilarities introduced by varying presence of contrast and inserted medical instruments highly affect the accuracy of existing registration algorithms.

A second aim of IGI is to locate the instrument within a 3D model of the patient in order to support complex navigation and positioning tasks. The automatic image-based tracking of such devices requires a prior detection of these within the intraoperative images. Instead of employing existing filtering approaches, the idea in this project is to employ background subtraction approaches.

In this project, you are supposed to analyze the applicability of background subtraction for X-ray images and, if necessary, come up with adaptation suggestions. The analysis can be performed with Matlab or C++ programming.

If you are interested please send your up-to-date CV to .


Students.ProjectForm
Title: Independent Component Analysis for Device Detection in X-ray Images
Abstract: Most catheterization procedures are performed under constant 2D X-ray imaging. Image-guided intervention (IGI) solutions aim at enhancing this 2D information by integrating the preoperatively acquired 3D patient scan into the intervention room. The automatic image-based tracking of such devices requires a prior detection of these within the intraoperative images. Instead of employing existing filtering approaches, the idea in this project is to analyze the applicability of Independent Component Analysis (ICA).
Student: Daniele Volpi
Director: Nassir Navab
Supervisor: Stefanie Demirci
Type: IDP/Klinisches Anwendungsprojekt
Area: Segmentation
Status: finished
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Finish:  
Thesis (optional):  
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Edit | Attach | Refresh | Diffs | More | Revision r1.2 - 13 Jul 2015 - 12:51 - StefanieDemirci