Abstract
Stability is of utmost importance to a wide range of phase-sensitive processing techniques. In Doppler optical coherence tomography and optical coherence elastography, in addition to defocus and aberration correction techniques such as interferometric synthetic aperture microscopy and computational/digital adaptive optics, a precise understanding of the system and sample stability helps to guide the system design and choice of imaging parameters. This article focuses on methods to accurately and quantitatively measure the stability of an imaging configuration in vivo. These methods are capable of partially decoupling axial from transverse motion and are compared against the stability requirements for computed optical interferometric tomography laid out in the first part of this article.
Highlights
Phase sensitive processing techniques such as Doppler optical coherence tomography (OCT) [1, 2], optical micro-angiography (OMAG) [3], phase variance OCT [4], magnetomotive OCT [5], quantitative optical phase microscopy [6], in addition to elastography techniques such as acoustic radiation force (ARF) optical coherence elastography (OCE) [7], magnetomotive OCE [8, 9], air puff OCE [10], and computed optical interferometric techniques such as interferometric synthetic aperture microscopy (ISAM) [11,12,13], computational adaptive optics (CAO) [14, 15], digital adaptive optics (DAO) [16], and holoscopy [17, 18] all share the common requirement of stability
A stability assessment using a partial reflector is an important measurement to make for any phase sensitive system, as the results can be compared with the expected theoretical performance to ensure the source and/or reference arm are not limiting factors to stability or significant contributors to noise in the system
The ability to quantitatively analyze the axial motion and transverse motion separately provided insight into the manner in which instabilities arise in the measured data
Summary
Phase sensitive processing techniques such as Doppler optical coherence tomography (OCT) [1, 2], optical micro-angiography (OMAG) [3], phase variance OCT [4], magnetomotive OCT [5], quantitative optical phase microscopy [6], in addition to elastography techniques such as acoustic radiation force (ARF) optical coherence elastography (OCE) [7], magnetomotive OCE [8, 9], air puff OCE [10], and computed optical interferometric techniques such as interferometric synthetic aperture microscopy (ISAM) [11,12,13], computational adaptive optics (CAO) [14, 15], digital adaptive optics (DAO) [16], and holoscopy [17, 18] all share the common requirement of stability. Most analyses end here quoting only a single number for the phase stability of a system, a broader range of instabilities are present in optical systems which are important to consider but cannot be measured using a partial reflector These include instabilities such as those from the scanning optics and most types of sample motion. Stability assessments have been performed by scanning/imaging a controlled tissue phantom (often uniformly scattering) [1, 22] in an attempt to measure a wider range of instabilities such as scanning jitter or irregularities [22, 28] These methods are typically used after the source and reference arm have been confirmed to be acceptably stable using a mirror or partial reflector. This way, the effects of motion on reconstructions can be avoided to reduce the need for post-processed corrections where possible
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