# Review on Retrospective Procedures to Correct Retinal Motion Artefacts in OCT Imaging
## 4 Chronological Review of Retrospective Approaches
### [2012-2014]
Quantitative evaluation was performed using data acquired from 73 healthy and glaucomatous eyes using SD-OCT systems. The algorithm was evaluated measuring retinal thickness, and comparing the results with the previous approach [71] and with the volumes without registration. In addition, the repeatability was evaluated, comparing several independent OCT volumes of the same subject by means of global measures, such as MI of the volumes, and local ones, such as comparison of vessels and layers. **[PERSON] et al. **[79]**(**2014**) proposed a method to correct motion artefacts using a single volume scan while still retaining the overall shape of the retina. It is stated that a volume acquired from a healthy individual should be mostly locally symmetric along the axial scan direction (coronal plane). Thus, the appearance of a small window in the fast scan direction should be similar to the appearance in the slow scan direction. In this study, a set of 100 macula centred SD-OCT volumes of two diferent SD-OCT scanners from patients with central retinal vein occlusion were used. The estimate of the local retina curvature by a preliminary segmentation of the RPE was obtained as a pre-registration step. Hence, a window in the fast and slow scan directions were selected and the local curvature was obtained by performing linear regression using the least-squares method. The axial correction was performed by shifting each A-scan along the depth axis based on the minimum sum of squared distances between the local and fitted curvature. In order to compensate for lateral motions (fast axis), local pairwise phase correlation between B-scans was calculated. The method was qualitatively validated by a group of trained OCT grading experts on 100 SD-OCT scans and quantitatively validated using a set of synthetic SD-OCT volumes. Furthermore, the motion compensation estimation by the proposed method was compared with a hardware eye tracker on 100 SD-OCT volumes. **[PERSON] et al. **[49]**(**2014**) proposed a registration method for pathological retinal 3D SD-OCT volumes based on Coherent Point Drift (CPD) [91]. Pre-processing included flattening of the B-scans to accurately locate the RPE layer and obtain its projection, denoising using a block matching based sparse transform [92], removal of non-vessel shadows, and vessel segmentation including its shadows. The motion correction algorithm defined two point sets, source and target 3D vessel center lines. One of the sets represents the Gaussian mixture model (GMM) centroids, and the other represents the data points. The sets are aligned solving a probability density estimation problem. Affine and non-rigid registrations were examined here. The optimization for affine was unconstrained, whereas, for non-rigid, a regularization of the norm of the displacement function [91] based on the motion coherence theory [93] was used. To evaluate registration performance, qualitative analysis of the transformed point set bifurcations by experienced graders was performed. A better result was observed of the non-rigid transformations. In addition, a total of 15 unique 3D SD-OCT fovea-centred diseased volumes were used for testing registration performance by calculating the modified Hausdorff and Mahalanobis distances [94] between point sets prior and post registration. The point set distance was expected to decrease post registration as the retinal vessels become aligned.