Markus A. Mayer

Motion correction in optical coherence tomography volumes on a per A-scan basis using orthogonal scan patterns

High speed Optical Coherence Tomography (OCT) has made it possible to rapidly capture densely sampled 3D volume data. One key application is the acquisition of high quality in vivo volumetric data sets of the human retina. Since the volume is acquired in a few seconds, eye movement during the scan process leads to distortion, which limits the accuracy of quantitative measurements using 3D OCT data. In this paper, we present a novel software based method to correct motion artifacts in OCT raster scans. Motion compensation is performed retrospectively using image registration algorithms on the OCT data sets themselves. Multiple, successively acquired volume scans with orthogonal fast scan directions are registered retrospectively in order to estimate and correct eye motion. Registration is performed by optimizing a large scale numerical problem as given by a global objective function using one dense displacement field for each input volume and special regularization based on the time structure of the acquisition process. After optimization, each volume is undistorted and a single merged volume is constructed that has superior signal quality compared to the input volumes. Experiments were performed using 3D OCT data from the macula and optic nerve head acquired with a high-speed ultra-high resolution 850 nm spectral OCT as well as wide field data acquired with a 1050 nm swept source OCT instrument. Evaluation of registration performance and result stability as well as visual inspection shows that the algorithm can correct for motion in all three dimensions and on a per A-scan basis. Corrected volumes do not show visible motion artifacts. In addition, merging multiple motion corrected and registered volumes leads to improved signal quality. These results demonstrate that motion correction and merging improves image quality and should also improve morphometric measurement accuracy from volumetric OCT data.

Retinal Nerve Fiber Layer Segmentation on FD-OCT Scans of Normal Subjects and Glaucoma Patients

Automated measurements of the retinal nerve fiber layer thickness on circular OCT B-Scans provide physicians additional parameters for glaucoma diagnosis. We propose a novel retinal nerve fiber layer segmentation algorithm for frequency domain data that can be applied on scans from both normal healthy subjects, as well as glaucoma patients, using the same set of parameters. In addition, the algorithm remains almost unaffected by image quality. The main part of the segmentation process is based on the minimization of an energy function consisting of gradient and local smoothing terms. A quantitative evaluation comparing the automated segmentation results to manually corrected segmentations from three reviewers is performed. A total of 72 scans from glaucoma patients and 132 scans from normal subjects, all from different persons, composed the database for the evaluation of the segmentation algorithm. A mean absolute error per A-Scan of 2.9 µm was achieved on glaucomatous eyes, and 3.6 µm on healthy eyes. The mean absolute segmentation error over all A-Scans lies below 10 µm on 95.1% of the images. Thus our approach provides a reliable tool for extracting diagnostic relevant parameters from OCT B-Scans for glaucoma diagnosis.

Wavelet denoising of multiframe optical coherence tomography data

We introduce a novel speckle noise reduction algorithm for OCT images. Contrary to present approaches, the algorithm does not rely on simple averaging of multiple image frames or denoising on the final averaged image. Instead it uses wavelet decompositions of the single frames for a local noise and structure estimation. Based on this analysis, the wavelet detail coefficients are weighted, averaged and reconstructed. At a signal-to-noise gain at about 100% we observe only a minor sharpness decrease, as measured by a full-width-half-maximum reduction of 10.5%. While a similar signal-to-noise gain would require averaging of 29 frames, we achieve this result using only 8 frames as input to the algorithm. A possible application of the proposed algorithm is preprocessing in retinal structure segmentation algorithms, to allow a better differentiation between real tissue information and unwanted speckle noise.

Retinal optical coherence tomography image enhancement via shrinkage denoising using double-density dual-tree complex wavelet transform

Abstract. Image enhancement of retinal structures, in optical coherence tomography (OCT) scans through denoising, has the potential to aid in the diagnosis of several eye diseases. In this paper, a locally adaptive denoising algorithm using double-density dual-tree complex wavelet transform, a combination of the double-density wavelet transform and the dual-tree complex wavelet transform, is applied to reduce speckle noise in OCT images of the retina. The algorithm overcomes the limitations of commonly used multiple frame averaging technique, namely the limited number of frames that can be recorded due to eye movements, by providing a comparable image quality in significantly less acquisition time equal to an order of magnitude less time compared to the averaging method. In addition, improvements of image quality metrics and 5 dB increase in the signal-to-noise ratio are attained.

Analysis of Visual Appearance of Retinal Nerve Fibers in High Resolution Fundus Images: A Study on Normal Subjects

The retinal ganglion axons are an important part of the visual system, which can be directly observed by fundus camera. The layer they form together inside the retina is the retinal nerve fiber layer (RNFL). This paper describes results of a texture RNFL analysis in color fundus photographs and compares these results with quantitative measurement of RNFL thickness obtained from optical coherence tomography on normal subjects. It is shown that local mean value, standard deviation, and Shannon entropy extracted from the green and blue channel of fundus images are correlated with corresponding RNFL thickness. The linear correlation coefficients achieved values 0.694, 0.547, and 0.512 for respective features measured on 439 retinal positions in the peripapillary area from 23 eyes of 15 different normal subjects.

Quality-Guided Denoising for Low-Cost Fundus Imaging

The restoration of noisy images is an essential pre-processing step in many medical applications to ensure sufficient quality for diagnoses. In this paper we present a new quality-guided approach for denoising of eye fundus images that suffer from high noise levels. The denoising is based on image sequences and an adaptive frame averaging approach. The novelty of the method is that it takes an objective image quality criteria to assess the different frames and tries to maximize the quality of the resulting image. It can be implemented in an incremental manner which allows real-time denoising. We evaluated our approach on real image sequences captured by a low-cost fundus camera and obtained competitive results to a state-of-the-art method in terms of signal-to-noise ratio whereas our method performs denoising about four times faster.

Atypical retardation patterns in scanning laser polarimetry are associated with low peripapillary choroidal thickness.

PURPOSE Scanning laser polarimetry (SLP) results can be affected by an atypical retardation pattern (ARP). One reason for an ARP is the birefringence of the sclera. The purpose of this study was to investigate the influence of the peripapillary choroidal thickness (pChTh) on the occurrence of ARP. METHODS One hundred ten healthy subjects were investigated with SLP and spectral domain OCT. pChTh was measured in B-scan images at 768 positions using semiautomatic software. Values were averaged to 32 sectors and the total peripapillary mean. Subjects were divided into four groups according to the typical scan score (TSS) provided by the GDxVCC: group 1 TSS, 100; group 2 TSS, 90-99; group 3 TSS, 80-89; group 4 TSS, <80. RESULTS Mean pChTh (± SD) in 110 healthy subjects was 141 μm (±49 μm). There was a significant correlation between pChTh and TSS (r = 0.608; P < 0.001). In TSS groups 1 to 4, mean pChTh was 168 μm (±38 μm), 148 μm (± 48 μm), 119 μm (±35 μm), and 92 (±42 μm). Mean pChTh of TSS groups 3 and 4 was significantly lower than that of TSS group 1 (P < 0.001). CONCLUSIONS Low values of TSS resulting from the appearance of ARP in SLP are associated with low peripapillary choroidal thickness. Reduced choroidal thickness may result in an increased amount of confounding light getting to the SLP light detectors.