2005
DOI: 10.1364/josaa.22.001132
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Task-based optimization and performance assessment in optical coherence imaging

Abstract: Optimization of an optical coherence imaging (OCI) system on the basis of task performance is a challenging undertaking. We present a mathematical framework based on task performance that uses statistical decision theory for the optimization and assessment of such a system. Specifically, we apply the framework to a relatively simple OCI system combined with a specimen model for a detection task and a resolution task. We consider three theoretical Gaussian sources of coherence lengths of 2, 20, and 40 microm. F… Show more

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Cited by 25 publications
(28 citation statements)
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“…Statistical decision theory was introduced into time domain OCT for classification tasks [6,7]. We recently reported on key results of using statistical decision theory to estimate tear film thickness [8].…”
Section: Introductionmentioning
confidence: 99%
“…Statistical decision theory was introduced into time domain OCT for classification tasks [6,7]. We recently reported on key results of using statistical decision theory to estimate tear film thickness [8].…”
Section: Introductionmentioning
confidence: 99%
“…the amount of light reflected, absorbed, and scattered are generally polarization dependent [10]. The temporal coherence plays an important role in some imaging applications as it represents the axial point spread function of the imaging system as for example in Optical Coherence Tomography (OCT) [11][12][13] and Optical Coherence Microscopy (OCM) [14]. Both polarization and coherence can be changed when a light beam propagates through the medium, e.g.…”
Section: Discussionmentioning
confidence: 99%
“…[18][19][20] Also, the approach of optimizing OCT hardware has investigated based on the use of ROC curves and AUCs for specified tasks, such as detecting the refractive index changes in multiple layers. 21,22 Here, we establish an observer for the task of diagnosing edema, which is called spatiotemporal correlation (STC) that is applied to OCT images using a rabbit airway surgical model. To the authors' knowledge, this is the first attempt to statistically quantify the differentiable characteristics of airway edema from in-vivo OCT images.…”
Section: Introductionmentioning
confidence: 99%