Visual Evaluation of 3D Image Enhancement

Image enhancement in 2 dimension is actually a famous and used approach. However the technologies in image acquisition have developed and these techniques usually offer image volumes in 3 or more dimensions, as in computer tomography, CT and magnetic resonance imaging, MRI. Three dimensions could have 2 spatial coordinates and one temporal coordinate or three spatial coordinates as in 3D image volumes, that will be utilized in this dissertation work.

The goals of this project are; to identify a technique that makes the initial parameter configurations in the 3D image enhancement processing simpler, to compare 2D and 3D processed image volumes visualized with various visualization techniques and also to provide an example of the advantages with 3D image enhancement processing visualized with such techniques.

Contents: Visual Evaluation of 3D Image Enhancement

1 Introduction
1.1 Background
1.1.1 Visualization techniques in clinical use
1.2 Objectives
1.3 Thesis outline
I Local adaptive filtering
2 Local adaptive filtering
2.1 Image orientation
2.1.1 Mapping requirements
2.1.2 Interpretation of the orientation tensor
2.2 Calculation of the control tensor
2.2.1 The m-function
2.2.2 The µ-function
2.3 Generation of the adaptive filter
3 Enhancement parameter setting tool, T-morph
3.1 Initial parameter setting of the m-function
3.2 Initial parameter setting of the µ- function
3.3 Result of the parameter setting tool
3.4 Conclusions
II Visualization techniques
4 Visualization techniques
4.1 Multiplanar reformatting
4.2 Image-order volume rendering
4.2.1 Maximum intensity projection
4.3 Object-order volume rendering
5 Results visualization techniques
5.1 Visualization with slices
5.1.1 3D enhancement in test volume
5.2 Visualization with MIP
5.2.1 Evaluation of test volume
5.2.2 Evaluation of MRA renal arteries
5.2.3 Evaluation of MRA cerebral arteries
5.3 Visualization with volume rendering
5.3.1 Evaluation of MRA renal arteries
5.3.2 Evaluation of MRA cerebral arteries
5.4 Conclusions…

Source: Linköping University

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