Program Information
Image Quality Models in Advanced CT Applications
J Siewerdsen
R Nishikawa
I Cunningham
G Chen
F Bochud
J Siewerdsen1*, R Nishikawa2*, I Cunningham3*, G Chen4*, F Bochud5*, (1) Johns Hopkins University, Baltimore , MD, (2) University Chicago, Chicago, IL, (3) Robarts Research Institute, London, ON, (4) University of Wisconsin, Madison, WI, (5) Lausanne University Hospital, Lausanne, Switzerland
TU-E-103-1 Tuesday 2:00PM - 3:50PM Room: 103The last decade saw the development of new x-ray tomographic imaging technologies, such as flat-panel detector cone-beam CT and tomosynthesis, now prevalent in applications ranging from diagnostic imaging to image-guided interventions. Such technologies proceeded in stride with models of imaging performance developed to provide a rigorous understanding of the factors governing image quality and help accelerate system design and translation. The decade ahead promises important advances - for example: statistical and iterative model-based image reconstruction; dual-energy and spectral tomography; photon counting detectors; phase contrast tomography; and understanding the performance of model and real observers in the context of volumetric data. The theoretical models of imaging performance now developing alongside such advanced technologies are the topic of this symposium. Dr. Nishikawa will introduce the broad and challenging landscape of such technologies and applications. Dr. Siewerdsen will discuss image quality models for dual-energy CT and the extension from conventional filtered backprojection to statistical / iterative reconstruction methods. Dr. Cunningham will describe the development of cascaded systems analysis for new photon counting detector systems. Dr. Chen will demonstrate how image quality models and performance measurement in x-ray (absorption) CT can be extended to differential phase-contrast CT. Finally, Dr. Bochud will address the performance of observers in volumetric data, highlighting newly appreciated factors that are distinct from conventional models and understanding in the context of 2D (or single slice) image interpretation.
Learning Objectives:
1. Understand the growing landscape of advanced tomographic imaging technologies and applications.
2. Understand how image quality models developed over the last decade for CT, cone-beam CT, and tomosynthesis can be extended to:
a.) dual-energy / spectral CT
b.) statistical and iterative image reconstruction
c.) photon counting detectors
d.) differential phase contrast CT
3. Understand the distinctions and new considerations in observer performance and image quality assessment in volumetric data.
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Funding Support, Disclosures, and Conflict of Interest: National Institutes of Health. Carestream Health. Siemens Healthcare.
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