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Papers Published

1. Fang, L; Li, S; Cunefare, D; Farsiu, S, Segmentation Based Sparse Reconstruction of Optical Coherence Tomography Images., IEEE transactions on medical imaging, vol. 36 no. 2 (February, 2017), pp. 407-421 [doi] .
   (last updated on 2024/12/31)

   Abstract:
   We demonstrate the usefulness of utilizing a segmentation step for improving the performance of sparsity based image reconstruction algorithms. In specific, we will focus on retinal optical coherence tomography (OCT) reconstruction and propose a novel segmentation based reconstruction framework with sparse representation, termed segmentation based sparse reconstruction (SSR). The SSR method uses automatically segmented retinal layer information to construct layer-specific structural dictionaries. In addition, the SSR method efficiently exploits patch similarities within each segmented layer to enhance the reconstruction performance. Our experimental results on clinical-grade retinal OCT images demonstrate the effectiveness and efficiency of the proposed SSR method for both denoising and interpolation of OCT images.