Image artifacts resulting from motion have been important topics of research in nearly all medical imaging modalities because they may degrade image quality and cause inaccurate clinical interpretation of images [1
]. Artifacts can arise when the object being imaged is moved during data acquisition but is assumed stationary in the image reconstruction process. In each imaging modality, motion artifacts can present in different forms and with different magnitudes. Understanding basic motion effects in a particular imaging method is an essential step toward the development of techniques to avoid or compensate resulting artifacts.
Optical coherence tomography (OCT) is a relatively new imaging modality using light for highly-sensitive imaging of a biological sample with high spatial resolution [5
]. OCT was originally developed based on low coherence interferometry [7
] where the time delay of optical echoes is determined using a low-coherence optical source and a delay-scanning interferometer. Optical interferometric imaging methods using frequency domain ranging have recently received considerable interest due to their high image acquisition speed and sensitivity. Two frequency domain methods have been demonstrated to date: spectral-domain optical coherence tomography (SD-OCT) [8
] and optical frequency domain imaging (OFDI) [13
]. In SD-OCT, the spectral interference fringe is measured in the spatial domain by means of a diffraction grating and a charge-coupled device (CCD) array. In OFDI, the spectral fringe is mapped to the time domain by use of a frequency-swept light source and is measured with a photodetector as a function of time. Since each data point of the spectral fringe links to the corresponding spatial frequency component of the depth profile of the sample, the axial line of an image (A-line) is obtained by performing a discrete Fourier transform of the acquired data. Since the Fourier transform process involves integration of the entire data set obtained in a single A-line period, the signal-to-noise ratio (SNR) is enhanced relative to time domain ranging [16
]. This improvement in SNR is particularly advantageous for applications requiring high image acquisition rates such as screening for disease and surveillance of large tissue volumes. It is, however, conceivable that the integration effect enhances the sensitivity to sample motion because the motion-induced change in signal is also integrated over the entire A-line acquisition period.
While both SD-OCT and OFDI are based on the same fundamental principle of optical interferometric imaging, the specifics of motion effects are quite different because of distinct signal acquisition methods. SD-OCT measures the interference signal in a time-integrated manner; however, OFDI obtains the signal as a function of time. In SD-OCT, for instance, a path length change in the interferometer results in phase drift in the interference fringe [18
]. If the phase drifts over more than π during a single A-line acquisition, the measured amplitude of the interference fringe can be considerably diminished, resulting in a degradation of SNR. A question may also arise whether this fringe washout can occur simply by scanning a probe beam over a stationary sample if the sample has internal structures with spatially varying depths. In biological samples, the mean depth to a particular structure may change by a large number of optical wavelengths between A-lines by beam scanning. In OFDI, the signal modulation frequency is uniquely related to depth in a sample [22
]. In terms of signal acquisition and processing, OFDI is analogous to conventional magnetic resonance imaging (MRI) [1
] in which the spatial position is encoded in the spin rotation frequency by using gradient magnetic fields. Therefore, it is expected that the motion effects in OFDI may be similar to those in MRI.
In this paper, we describe the results of theoretical and experimental investigation on the motion effects in SD-OCT and OFDI. Section 2 concerns SD-OCT, and Section 3 describes OFDI. For each of the imaging methods, we describe a theoretical analysis, experimental verifications, and discussion on the implications of the motion effects in clinical applications. Section 4 summarizes the results.