@InProceedings{8081164,
  author = {A. Stankiewicz and T. Marciniak and A. Dąbrowski and M. Stopa and E. Marciniak},
  booktitle = {2017 25th European Signal Processing Conference (EUSIPCO)},
  title = {Volumetric segmentation of human eye blood vessels based on OCT images},
  year = {2017},
  pages = {36-40},
  abstract = {In this paper we present a method for volumetric segmentation of retinal vessels based on 3D OCT images of human macula. The proposed hybrid method is comprised of two steps: detailed extraction of superficial blood vessels indicators visible in 2D projection of retina layers followed by an axial inspection of inner retina to determine exact depth position of each vessel. The segmentation procedure is improved by application of block-matching and 4D filtering (BM4D) algorithm for noise reduction. The 3D reconstruction of vascular structure was performed for 10 normal subjects examined with Avanti AngioVue OCT device. The automated segmentation results were validated against the manual segmentation performed by an expert giving the accuracy of 95.2%.},
  keywords = {biomedical optical imaging;blood vessels;eye;image denoising;image filtering;image matching;image reconstruction;image segmentation;medical image processing;volumetric segmentation;human eye blood vessels;OCT images;retinal vessels;retina layers;axial inspection;inner retina;4D filtering algorithm;manual segmentation;automated segmentation;human macula images;superficial blood vessels indicator extraction;block-matching algorithm;noise reduction;3D vascular structure reconstruction;avanti angiovue OCT device;Image segmentation;Retina;Three-dimensional displays;Signal processing algorithms;Biomedical imaging;Two dimensional displays;Blood vessels;retina vessels segmentation;fundus reconstruction;optical coherence tomography (OCT);3D visualization},
  doi = {10.23919/EUSIPCO.2017.8081164},
  issn = {2076-1465},
  month = {Aug},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2017/papers/1570347185.pdf},
}

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The proposed hybrid method is comprised of two steps: detailed extraction of superficial blood vessels indicators visible in 2D projection of retina layers followed by an axial inspection of inner retina to determine exact depth position of each vessel. The segmentation procedure is improved by application of block-matching and 4D filtering (BM4D) algorithm for noise reduction. The 3D reconstruction of vascular structure was performed for 10 normal subjects examined with Avanti AngioVue OCT device. 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Stankiewicz and T. Marciniak and A. Dąbrowski and M. Stopa and E. Marciniak},\n booktitle = {2017 25th European Signal Processing Conference (EUSIPCO)},\n title = {Volumetric segmentation of human eye blood vessels based on OCT images},\n year = {2017},\n pages = {36-40},\n abstract = {In this paper we present a method for volumetric segmentation of retinal vessels based on 3D OCT images of human macula. The proposed hybrid method is comprised of two steps: detailed extraction of superficial blood vessels indicators visible in 2D projection of retina layers followed by an axial inspection of inner retina to determine exact depth position of each vessel. The segmentation procedure is improved by application of block-matching and 4D filtering (BM4D) algorithm for noise reduction. The 3D reconstruction of vascular structure was performed for 10 normal subjects examined with Avanti AngioVue OCT device. 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