BaOctreeLineIntegrals

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

Bachelor's thesis: Octree-based line integral algorithms for X-ray Computed Tomography

Project by: Philipp Bock
Advisor: Tobias Lasser

Abstract

X-ray Computed Tomography (CT) has been essential for medical diagnostics for decades now. Based on accurate forward modeling and solving the inverse problem, tomographic reconstruction is the algorithmic framework to enable X-ray CT. Central to the forward model is the projector and back-projector pair computing discretized line integrals, which model the interactions of X-rays with the sample and the acquisition geometry. Along with high computational demands, accuracy is paramount.

Tasks

Subject of this project is the efficient computation of accurate line integrals, which is the main computational complexity of any reconstruction algorithm in X-ray Computed Tomography. The aim of this work is to investigate octree-based volume representations, to enable very efficient ray tracing in order to compute discretized line integrals. An algorithm similar to the popular Joseph's method should be developed, implemented and evaluated against other standard methods, both in terms of accuracy and performance (multi-core CPU-based).

Requirements

C++, parallel programming, some geometry knowledge

Contact


ProjectForm
Title: Octree-based line integral algorithms for X-ray Computed Tomography
Abstract: X-ray Computed Tomography (CT) has been essential for medical diagnostics for decades now. Based on accurate forward modeling and solving the inverse problem, tomographic reconstruction is the algorithmic framework to enable X-ray CT. Central to the forward model is the projector and back-projector pair computing discretized line integrals, which model the interactions of X-rays with the sample and the acquisition geometry. Along with high computational demands, accuracy is paramount.
Student: Philipp Bock
Director: Tobias Lasser
Supervisor:  
Type: Bachelor Thesis
Area: Medical Imaging
Status: running
Start: 2018/11/15
Finish: 2019/03/15
Thesis (optional):  
Picture:  


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