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Program Information

Assessment of Image Quality in the New CT


J Siewerdsen

J Fessler

K Myers

J Siewerdsen1*, J Fessler2*, K Myers3*, (1) Johns Hopkins University, Baltimore, MD, (2) University of Michigan, Ann Arbor, MI, (3) Office of Science and Engineering Labs, CDRH, FDA, Silver Spring, MD

MO-F-217BCD-1 Monday 4:30:00 PM - 6:00:00 PM Room: 217BCD

The emergence of fully volumetric CT imaging systems and statistical / iterative reconstruction methods present an immediate need for rigorous methods of image quality assessment. Major themes arising in the widespread utilization of such technologies include: 1.) the reduction of radiation dose in a manner that maintains imaging performance with respect to the imaging task;
2.) the need for quantitative standards in image quality assessment appropriate to various vendor hardware and reconstruction systems;
3.) imaging performance metrics that provide meaningful descriptors of fully 3D spatial resolution and noise characteristics;
4.) the dependence of these metrics on acquisition technique, reconstruction parameters, and their applicability (or lack thereof) to novel reconstruction methods that may defy conventional metrics founded in assumptions of linearity and shift invariance; and
5.) methods for physical measurement (e.g., phantoms) and theoretical analysis of image quality for these new and emerging CT technologies and their implications for dose reduction.

Learning Objectives
1.) Understand the methods and metrics of image quality assessment for fully volumetric (cone-beam) CT imaging using 3D filtered backprojection, including analysis of the 3D NPS, NEQ, and detectability index.
2.) Understand the limitations and assumptions of such metrics with respect to linearity, stationarity, and novel reconstruction techniques.
3.) Gain an understanding of how rigorous assessment of imaging performance can guide technique optimization, dose reduction, and the development of new CT technologies and applications.
4.) Understand the factors of image quality assessment in nonlinear statistical / model-based 3D reconstruction techniques, including PSF and covariance estimation in nonstationary systems.
5.) Gain perspective on image quality assessment standards, including methods for dose and image quality measurement on different vendor platforms and the implications for dose reduction.


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