System Optimization and Iterative Image Reconstruction in Photoacoustic Computed Tomography for Breast Imaging

<p>Photoacoustic computed tomography(PACT), also known as optoacoustic tomography (OAT), is an emerging imaging technique that has developed rapidly in recent years. The combination of the high optical contrast and the high acoustic resolution of this hybrid imaging technique makes it a promising candidate for human breast imaging, where conventional imaging techniques including X-ray mammography, B-mode ultrasound, and MRI suffer from low contrast, low specificity for certain breast types, and additional risks related to ionizing radiation. Though significant works have been done to push the frontier of PACT breast imaging, it is still challenging to successfully build a PACT breast imaging system and apply it to wide clinical use because of various practical reasons. First, computer simulation studies are often conducted to guide imaging system designs, but the numerical phantoms employed in most previous works consist of simple geometries and do not reflect the true anatomical structures within the breast. Therefore the effectiveness of such simulation-guided PACT system in clinical experiments will be compromised. Second, it is challenging to design a system to simultaneously illuminate the entire breast with limited laser power. Some heuristic designs have been proposed where the illumination is non-stationary during the imaging procedure, but the impact of employing such a design has not been carefully studied. Third, current PACT imaging systems are often optimized with respect to physical measures such as resolution or signal-to-noise ratio (SNR). It would be desirable to establish an assessing framework where the detectability of breast tumor can be directly quantified, therefore the images produced by such optimized imaging systems are not only visually appealing, but most informative in terms of the tumor detection task. Fourth, when imaging a large three-dimensional (3D) object such as the breast, iterative reconstruction algorithms are often utilized to alleviate the need to collect densely sampled measurement data hence a long scanning time. However, the heavy computation burden associated with iterative algorithms largely hinders its application in PACT breast imaging. This dissertation is dedicated to address these aforementioned problems in PACT breast imaging. A method that generates anatomically realistic numerical breast phantoms is first proposed to facilitate computer simulation studies in PACT. The non-stationary illumination designs for PACT breast imaging are then systematically investigated in terms of its impact on reconstructed images. We then apply signal detection theory to assess different system designs to demonstrate how an objective, task-based measure can be established for PACT breast imaging. To address the</p><p>slow computation time of iterative algorithms for PACT imaging, we propose an acceleration method that employs an approximated but much faster adjoint operator during iterations, which can reduce the computation time by a factor of six without significantly compromising image quality. Finally, some clinical results are presented to demonstrate that the PACT breast imaging can resolve most major and fine vascular structures within the breast, along with some pathological biomarkers that may indicate tumor development.</p>

Name thesis:degree_name

Doctor of Philosophy (PhD)

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Biomedical Engineering

Year dc:date.available

2017

Author dc:creator

• Lou, Yang

Contributors dc:contributor

• Mark A. Anastasio
• Joseph Culver, Barani Raman, Jung-Tsung Shen, Quing Zhu,

• breast imaging
• computational imaging
• image reconstruction
• iterative method
• photoacoustic computed tomography
• Bioimaging and Biomedical Optics
• Biomedical Engineering and Bioengineering
• Other Physics
• Physics

Statement dc:rights

• I have not registered my thesis with the U.S. Copyright Office, and do not intend to.

Language dc:language

English (en)

Identifier

https://openscholarship.wustl.edu/eng_etds/285

OAI identifier oai:identifier

oai:openscholarship.wustl.edu:eng_etds-1293