Perceptually Relevant Measurements in Tomosynthesis Imaging

Tissue structures and imaging system parameters are major factors that influence the ability of radiologists to find and identify malignancies. For example, parameters relevant to mammography like radiation dose, breast density and thickness, pixel size, arc span and number of projections in the case of digital breast tomosynthesis (aka 3D mammography) can alter the cancer screening diagnosis. Therefore, it is necessary to find which configuration is best so that least number of malignancies are missed by the radiologists. They examine hundreds of radiographs every day and sometimes there is a potential to misclassify the images. By understanding the image properties in relation to human perceptual mechanisms, we can find the optimal configurations to reduce misdiagnosis. The focus of this thesis is to characterize digital breast tomosynthesis (DBT) images using image quality metrics and eye gaze analysis and to explore how these metrics relate to abnormality detection performance and diagnostic errors. The first part of this thesis evaluates the relevance of noise power spectrum (NPS) based metrics in characterizing the DBT images and their relation to human observer diagnosis performance. The NPS based power-law exponent beta was hypothesized to quantify tissue structural overlap and to use as a surrogate for diagnostic performance in x-ray imaging. We showed that random noise and system configurations influence this parameter and do not correlate with human observer performance in DBT imaging and hence cannot be used as a surrogate for diagnostic performance while the power-law magnitude (K) showed a strong correlation. Next, we investigated the impact of phantom structural variations on the estimation of DBT optimal configurations in virtual imaging trials (VITs). Our results indicate that phantoms should be designed to resemble the patients’ anatomical structures accurately and should be evaluated for their realism and sufficiency in the use of VITs. Finally, to further our understanding of the relation between different system parameters and human perceptual mechanisms, gaze analysis was conducted. To this end, we developed a graphical user interface for an eye-tracking tool to conduct eye-tracking studies and estimate eye gaze metrics and fixation regions. Our results indicate that along with diagnostic performance other perceptual aspects such as image reading time can be considered for system optimization. Our gaze analysis suggests that gaze metrics correlate with diagnostic performance and task difficulty and could help understand the difficulty levels in a VIT.

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

Doctoral

Discipline thesis:degree_discipline

Biomedical Engineering

Grantor

University of Houston

Year dc:date.issued

2022

Author dc:creator

• Kavuri, Amareswararao

Advisor dc:contributor.advisor

• Das, Mini

Committee members dc:contributor.committeemember

• Francis, Joseph T.
• Gifford, Howard C.
• Hebert, Thomas J.
• Zhang, Yingchun

• Virtual imaging trial
• VIT
• VCT
• NPS
• Noise power spectrum
• Digital phantoms
• AUC
• Human observer study
• Digital breast tomosynthesis
• DBT
• Gaze metrics
• Perceptual error signatures
• Visual attention mechanisms
• Image processing filters
• Image quality metrics
• Task based assessment

Statement dc:rights

• The author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. UH Libraries has secured permission to reproduce any and all previously published materials contained in the work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/10657/14330

OAI identifier oai:identifier

oai:uh-ir.tdl.org:10657/14330