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Automated non-rigid registration and mosaicing for robust imaging of distinct retinal capillary beds using speckle variance optical coherence tomography.

Hendargo HC, Estrada R, Chiu SJ, Tomasi C, Farsiu S, Izatt JA - Biomed Opt Express (2013)

Bottom Line: Slight changes in the orientation of the subject's eye relative to the optical system between acquired volumes may result in non-rigid warping of the image.Thus, we use a B-spline based free form deformation method to automatically register variance images from multiple volumes to obtain a motion-free composite image of the retinal vessels.We extend this technique to automatically mosaic individual vascular images into a widefield image of the retinal vasculature.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA.

ABSTRACT
Variance processing methods in Fourier domain optical coherence tomography (FD-OCT) have enabled depth-resolved visualization of the capillary beds in the retina due to the development of imaging systems capable of acquiring A-scan data in the 100 kHz regime. However, acquisition of volumetric variance data sets still requires several seconds of acquisition time, even with high speed systems. Movement of the subject during this time span is sufficient to corrupt visualization of the vasculature. We demonstrate a method to eliminate motion artifacts in speckle variance FD-OCT images of the retinal vasculature by creating a composite image from multiple volumes of data acquired sequentially. Slight changes in the orientation of the subject's eye relative to the optical system between acquired volumes may result in non-rigid warping of the image. Thus, we use a B-spline based free form deformation method to automatically register variance images from multiple volumes to obtain a motion-free composite image of the retinal vessels. We extend this technique to automatically mosaic individual vascular images into a widefield image of the retinal vasculature.

No MeSH data available.


Enlarged view of images in Fig. 8 comparing the registered images to SVPs from a single volume. Motion artifacts are removed and visualization of the vasculature is enhanced in the registered images. A color encoded depth image is shown on the right, combining information from the registered images of the 3 vessel layers. Red indicates more superficial vessels while blue indicates deeper vessels.
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g009: Enlarged view of images in Fig. 8 comparing the registered images to SVPs from a single volume. Motion artifacts are removed and visualization of the vasculature is enhanced in the registered images. A color encoded depth image is shown on the right, combining information from the registered images of the 3 vessel layers. Red indicates more superficial vessels while blue indicates deeper vessels.

Mentions: Registration result from subject 1. Two X-fast and two Y-fast data sets were acquired. The original SVPs for each of the 3 main vessel layers are shown in the 4 left columns. The right most column shows results of image registration for each of the 3 layers. Each image covers a 2.5 × 2.5 mm scan area.


Automated non-rigid registration and mosaicing for robust imaging of distinct retinal capillary beds using speckle variance optical coherence tomography.

Hendargo HC, Estrada R, Chiu SJ, Tomasi C, Farsiu S, Izatt JA - Biomed Opt Express (2013)

Enlarged view of images in Fig. 8 comparing the registered images to SVPs from a single volume. Motion artifacts are removed and visualization of the vasculature is enhanced in the registered images. A color encoded depth image is shown on the right, combining information from the registered images of the 3 vessel layers. Red indicates more superficial vessels while blue indicates deeper vessels.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3675861&req=5

g009: Enlarged view of images in Fig. 8 comparing the registered images to SVPs from a single volume. Motion artifacts are removed and visualization of the vasculature is enhanced in the registered images. A color encoded depth image is shown on the right, combining information from the registered images of the 3 vessel layers. Red indicates more superficial vessels while blue indicates deeper vessels.
Mentions: Registration result from subject 1. Two X-fast and two Y-fast data sets were acquired. The original SVPs for each of the 3 main vessel layers are shown in the 4 left columns. The right most column shows results of image registration for each of the 3 layers. Each image covers a 2.5 × 2.5 mm scan area.

Bottom Line: Slight changes in the orientation of the subject's eye relative to the optical system between acquired volumes may result in non-rigid warping of the image.Thus, we use a B-spline based free form deformation method to automatically register variance images from multiple volumes to obtain a motion-free composite image of the retinal vessels.We extend this technique to automatically mosaic individual vascular images into a widefield image of the retinal vasculature.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA.

ABSTRACT
Variance processing methods in Fourier domain optical coherence tomography (FD-OCT) have enabled depth-resolved visualization of the capillary beds in the retina due to the development of imaging systems capable of acquiring A-scan data in the 100 kHz regime. However, acquisition of volumetric variance data sets still requires several seconds of acquisition time, even with high speed systems. Movement of the subject during this time span is sufficient to corrupt visualization of the vasculature. We demonstrate a method to eliminate motion artifacts in speckle variance FD-OCT images of the retinal vasculature by creating a composite image from multiple volumes of data acquired sequentially. Slight changes in the orientation of the subject's eye relative to the optical system between acquired volumes may result in non-rigid warping of the image. Thus, we use a B-spline based free form deformation method to automatically register variance images from multiple volumes to obtain a motion-free composite image of the retinal vessels. We extend this technique to automatically mosaic individual vascular images into a widefield image of the retinal vasculature.

No MeSH data available.