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1 July 2007 Adaptation of a support vector machine algorithm for segmentation and visualization of retinal structures in volumetric optical coherence tomography data sets
Robert Jozef Zawadzki, Alfred R. Fuller, David F. Wiley, Bernd Hamann, Stacey S. Choi, John S. Werner
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Journal of Biomedical Optics, Vol. 12, Issue 4, 041206 (July 2007). https://doi.org/10.1117/1.2772658
Abstract
Recent developments in Fourier domain—optical coherence tomography (Fd-OCT) have increased the acquisition speed of current ophthalmic Fd-OCT instruments sufficiently to allow the acquisition of volumetric data sets of human retinas in a clinical setting. The large size and three-dimensional (3D) nature of these data sets require that intelligent data processing, visualization, and analysis tools are used to take full advantage of the available information. Therefore, we have combined methods from volume visualization, and data analysis in support of better visualization and diagnosis of Fd-OCT retinal volumes. Custom-designed 3D visualization and analysis software is used to view retinal volumes reconstructed from registered B-scans. We use a support vector machine (SVM) to perform semiautomatic segmentation of retinal layers and structures for subsequent analysis including a comparison of measured layer thicknesses. We have modified the SVM to gracefully handle OCT speckle noise by treating it as a characteristic of the volumetric data. Our software has been tested successfully in clinical settings for its efficacy in assessing 3D retinal structures in healthy as well as diseased cases. Our tool facilitates diagnosis and treatment monitoring of retinal diseases.
©(2007) Society of Photo-Optical Instrumentation Engineers (SPIE)
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Robert Jozef Zawadzki, Alfred R. Fuller, David F. Wiley, Bernd Hamann, Stacey S. Choi, and John S. Werner "Adaptation of a support vector machine algorithm for segmentation and visualization of retinal structures in volumetric optical coherence tomography data sets," Journal of Biomedical Optics 12(4), 041206 (1 July 2007). https://doi.org/10.1117/1.2772658
Published: 1 July 2007
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Cited by 60 scholarly publications and 8 patents.
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KEYWORDS
Image segmentation
Visualization
Optical coherence tomography
Data acquisition
Eye
Visual analytics
Retina
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