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Appl. Sci. 2017, 7(8), 748;

Needle Segmentation in Volumetric Optical Coherence Tomography Images for Ophthalmic Microsurgery

Institut für Informatik, Technische Universität München, 85748 München, Germany
Carl Zeiss Meditec AG., 81379 München, Germany
School of Data and Computer Science, Sun Yat-Sen University, Guangzhou 510006, China
Augenklinik und Poliklinik, Klinikum rechts der Isar der Technische Universit München, 81675 München, Germany
Authors to whom correspondence should be addressed.
Received: 22 June 2017 / Revised: 17 July 2017 / Accepted: 18 July 2017 / Published: 25 July 2017
(This article belongs to the Special Issue Development and Application of Optical Coherence Tomography (OCT))
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Needle segmentation is a fundamental step for needle reconstruction and image-guided surgery. Although there has been success stories in needle segmentation for non-microsurgeries, the methods cannot be directly extended to ophthalmic surgery due to the challenges bounded to required spatial resolution. As the ophthalmic surgery is performed by finer and smaller surgical instruments in micro-structural anatomies, specifically in retinal domains, difficulties are raised for delicate operation and sensitive perception. To address these challenges, in this paper we investigate needle segmentation in ophthalmic operation on 60 Optical Coherence Tomography (OCT) cubes captured during needle injection surgeries on ex-vivo pig eyes. Furthermore, we developed two different approaches, a conventional method based on morphological features (MF) and a specifically designed full convolution neural networks (FCN) method, moreover, we evaluate them on the benchmark for needle segmentation in the volumetric OCT images. The experimental results show that FCN method has a better segmentation performance based on four evaluation metrics while MF method has a short inference time, which provides valuable reference for future works. View Full-Text
Keywords: needle segmentation; ophthalmic microsurgery; Optical Coherence Tomography needle segmentation; ophthalmic microsurgery; Optical Coherence Tomography

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Zhou, M.; Roodaki, H.; Eslami, A.; Chen, G.; Huang, K.; Maier, M.; Lohmann, C.P.; Knoll, A.; Nasseri, M.A. Needle Segmentation in Volumetric Optical Coherence Tomography Images for Ophthalmic Microsurgery. Appl. Sci. 2017, 7, 748.

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