# Review on Retrospective Procedures to Correct Retinal Motion Artefacts in OCT Imaging
## 5 Discussion
In addition, the performance of the registration is not clear when pathological data are analysed, emphasizing the importance of proper validation techniques. Unlike other imaging technologies, retinal OCT data do not have a ground truth reference to validate the registration. Therefore, qualitative techniques and, specifically, visual inspection, have been the main validation techniques used to infer the performance of the retrospective registration in OCT imaging. The low acquisition rate of the first OCT generation, TD-OCT, required to inspect the misalignments within each cross-sectional image. Since the introduction of SD-OCT, B-scans are obtained with acquisition rates comparable to the frequency of the drifts or microsaccades. Hence, both registration and validation have shifted towards the correction of misalignments handling the slow-axis (between adjacent B-scans). A smooth profile, similar to what can be observed in the fast-axis, is expected over the slow-axis. However, retinal pathologies such as age-related macular degeneration (AMD) or macular hole are likely to result in steep adjacent regions, which may be wrongly understood as consequence of a poor registration. In order to distinguish if the lack of smoothness is caused by motion or pathologies and, hence, if it must be corrected or not, the registration started to include the acquisition of additional orthogonal B-scans along the slow axis of the main image. Some authorsused these B-scans for validation, as a reference of the expected retinal profile on the volumetric OCT data. This provides a rough idea of the axial registration performance over the fast and slow planes, but not on the coronal plane. For the latter, en face images obtained by projecting the volumetric data can be used. The visualization of structures, such as the continuity of the blood vessels and the shapes of the optic disc or the fovea, gives hints on the performance of the registration algorithm. An easy way to infer the registration robustness through visual inspection is to use a checkerboard between two independent measurements of the same subject, either between cross-sectional or en face images. Although visual inspection gives a first insight on the registration accuracy, it is insufficient for evaluating the performance of registration algorithms because there is neither a standard reference nor a ground truth available. Additionally, it does not permit the optimization of an algorithm (e.g., fine-tuning registration parameters). Hence, as the dimension of volumetric datasets started to increase with the switch from TD-OCT to SD-OCT, quantitative validation techniques became an urgent need. Consequently, since 2007, a number of methods have been proposed, which have been categorized in this review as quantitative metrics (intensity-based or comparison of annotated structures), simulated data, and multi-modality comparison. One of the most widely used intensity-based techniques in the field of OCT registration is mutual information, which compares the intensity distribution of the histograms of the images. Regarding the comparison of annotated structures, two main groups can be distinguished: to compare the overlapping of volumes or surfaces and to compute the distances between a set of landmarks. In the first group, the most common formulation in the works that were reviewed is the Dice similarity coefficient. In the second group, there is a wider variety of metrics, as different distances have been used. One common application is to compare an OCT volume before and after registration, marking the same points (e.g., vessel bifurcations) in the B-scans from the original and registered volume. The distance between the same point in different B-scans is expected to decrease post registration, as the retinal structures become aligned. The metrics based on annotated structures can be computed using a manually labelled reference or a fully automatic approach. The first provides a ground truth but has the main drawbacks of being subjective and time-consuming.