# Review on Retrospective Procedures to Correct Retinal Motion Artefacts in OCT Imaging
## 5 Discussion
This motivated the development of new methods to correct axial misalignments seen across the slow axis of a volume scan. The cross-correlation metric remained a popular choice, and was used in combination with pairwise rigid and, later in 2008, affine transformations. The need of a reference led to the development of multimodality imaging, broadly raising the interest on feature-based registration. Rigid and non-rigid transformations were used to align common features between OCT and SLO or FP. Although it is assumed that SLO can be used as a ground truth, it is not completely free from movement artefacts due to its scanning pattern [64]. FP can be considered a better reference since the whole image is taken in a single shot. The introduction of retinal multimodality imaging allowed, for the first time, to have a reference for coronal misalignments. By the end of 2010, despite all the progress done, axial (fast and slow axis) misalignments remained a significant problem on OCT image reliability. Hence, changes on the acquisition protocols were suggested as a mean to obtain a reference for the registration. Based on the artefact difference between the slow and the fast-axis, a second volume, orthogonal to the first one, could be used to correct the axial misalignments over the slow axis in the main (reference) volume. Feature-based registration, focused on both the retinal layers and the blood vessel ridges, was used to correct these misalignments. The establishment of SD-OCT as a gold standard imaging modality in ophthalmology boosted its development to SS-OCT. The joint efforts of the scientific community on increasing the acquisition rate led to cross-sectional images that are nowadays being considered movement artefact free. Consequently, since 2015, the correction of the misalignments between A-scans handling the fast axis has significantly dropped, and most authors dedicated their efforts to correct between B-scans on both axis, between A-scans across the slow axis, and using the coronal plane. Moreover, these last years have also been marked by the wide adoption of OCT-A imaging, where small motion artifacts have shown a large impact on the angiographic image quality. Some methods have been proposed to correct motion artefacts in OCT-A en face imaging. For example, [PERSON] et al. [107] acquired two non-orthogonal en face angiograms and divided them into microsaccade-free parallel strips. Then, a rough registration based on large vessels and a fine registration based on small vessels were sequentially applied to register parallel strips into a composite image. Although some correction methods are based on the OCT-A en face imaging, the majority of the motion correction algorithms employ the techniques mentioned in this survey, which were developed and tested for correcting intrinsic retinal motion in conventional OCT imaging. For instance, the methodology proposed by [PERSON] et al. in 2012 [71] and later in 2014 [78] has been widely used as a standard correction in OCT-A imaging [13; 108; 109; 110; 111; 112; 113]. The fast rise of OCT-A as a non-invasive vascular imaging modality in clinical practice has brought up again the importance of proper and accurate registration in OCT imaging. Since OCT-A imaging results from the amplitude decorrelation or phase variance of two or more OCT images, it is fundamental to ensure that the OCT data are free of movement artefacts in order to provide reliable information of the retinal systemic system. The need of correcting the OCT-A images shows that, despite all the advances in motion correction since the introduction of OCT, more knowledge in the intrinsic retinal motion process, and more advanced and precise methods to correct these artefacts in OCT imaging are needed. Moreover, although the combination of a high acquisition speed, multi-imaging protocols for complementary data, and multi-modality, are reducing the retinal imaging artefacts to extremely low levels, the increase of the lateral and axial resolution is expected to bring new challenges to image registration.