Breast cancer continues to be the most frequently diagnosed cancer in Canadian women. Currently, mammography is the clinically accepted best modality for breast cancer detection and the regular use of screening has been shown to contribute to the reduced mortality. However, mammography suffers from several drawbacks which limit its sensitivity and specificity. As a potential solution, digital breast tomosynthesis (DBT) uses a limited number (typically 10-20) of low-dose x-ray projections to produce a three-dimensional tomographic representation of the breast. The reconstruction of DBT images is challenged by such incomplete sampling. The purpose of this thesis is to evaluate the effect of image acquisition parameters on image quality of DBT for various reconstruction techniques and to optimize these, with three specific goals: A) Develop a better power spectrum estimator for detectability calculation as a task-based image quality index; B) Develop a paired-view algorithm for artifact removal in DBT reconstruction; and C) Increase dose efficiency in DBT by reducing random noise.
A better power spectrum estimator was developed using a multitaper technique, which yields reduced bias and variance in estimation compared to the conventional moving average method. This gives us an improved detectability measurement with finer frequency steps. The paired-view scheme in DBT reconstruction provides better image quality than the commonly used sequential method. A simple ordering like the “side-to-side” method can achieve less artifact and higher image quality in reconstructed slices. The new denoising algorithm developed was applied to the projection views acquired in DBT before reconstruction. The random noise was markedly removed while the anatomic details were maintained. With the help of this artifact-removal technique used in reconstruction and the denoising method employed on the projection views, the image quality of DBT is enhanced and lesions should be more readily detectable.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/65768 |
| Date | 01 September 2014 |
| Creators | Wu, Gang |
| Contributors | Yaffe, Martin |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
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