My research interests are subjective and objective image/video quality assessment methods, and their use in optimizing and validating the image quality of medical imaging devices. I've grouped my work into the following categories, read on:
Objective measures are computer algorithms which measure the quality of an image or video and attempt to mimic or predict human judgement. Objective measures can be useful during the research and development phase of a new imaging device to optimize the selection and tuning of various acquisition, image/post processing, or display parameters.
My research in this area focuses on the development of a medical image quality metric and contribution to a general video quality metric:
The gold standard in medical image quality assessment is diagnostic performance studies - typically a receiver operating characteristic (ROC)-based assessment paradigm. These studies quantify how well users can conduct a specific task - usually their ability to discriminate between abnormal and normal cases (cases with and without lesions) - with a particular imaging system. Systems with better discriminative ability (e.g. higher AUC) are considered to have higher image quality.
My research in the area of diagnostic performance has focused on the evaluation of multi-slice (volumetric) image viewing:
In medical imaging, subjective QA is not a replacement for diagnostic studies, since it does not measure how useful an image is at doing its job: allowing the user to conduct a specific task, such as the diagnosis of a disease. Subjective QA may still be useful during the research and development phase of an imaging device to understand the relationship between imaging parameters and the user's perception/experience, or for finding thresholds at which differences become perceptible. However, it is important to realize that subjective preference may not necessarily correlate directly with diagnostic performance - this is an interesting topic for future research.
Subjective QA plays a larger role in non-medical applications, such as television or video streaming, since typically the goal in these applications is to develop imaging systems that produce visually appealing images and video.
I have conducted and contributed to subjective quality assessment studies in 4 medical domains and 1 materials science application to research the effects of subject expertise, image content, and imaging parameters on subjective quality preferences:
- Methodology for selecting stimuli for video quality assessment studies, applied to interventional cardiac x-ray imaging and laparoscopic surgery video (conference paper, [preprint pdf])
- Assessment of the perceived quality of interventional cardiac x-ray sequences (co-author on conference paper)
- Evaluation of the effects of expertise and content on the perceived quality of H.264/AVC compressed laparoscopic surgery video (conference paper, [preprint pdf])
- Subjective quality assessment of various degradations in stereoscopic medical images (co-author on conference paper)
- Assessment of the perceived quality of degraded digital pathology images (co-author on conference presentation)
- Subjective assessment of mechanical wear degradation for a materials science application (co-author on journal paper)
The user's performance and behavior while using an imaging device is another way to evaluate the impact of a new technology on a particular clinical task.
My research on user performance and behavior has focused on the following two applications:
This research has been partially or wholly funded thanks to the following grants: