Enhancement of nerve structure segmentation by a correntropy-based pre-image approach
Journal Title: TecnoLógicas - Year 2017, Vol 20, Issue 39
Abstract
Peripheral Nerve Blocking (PNB) is a commonly used technique forperformingregional anesthesia and managing pain. PNB comprises the administration of anestheticsin the proximity of a nerve. In this sense, the success of PNB procedures depends on an accurate location of the target nerve. Recently, ultrasound images (UI) havebeen widely used to locate nerve structures forPNB,since theyenable a non-invasive visualization of the target nerve and the anatomical structures around it. However, UIare affected by speckle noise, which makes it difficult to accuratelylocatea given nerve. Thus, it is necessary to perform a filtering step to attenuate the speckle noise without eliminating relevant anatomical details that are required for high-level tasks, suchas segmentation of nerve structures. In this paper, we propose an UI improvement strategy with the use of a pre-image-based filter. In particular, we map the input images bya nonlinear function (kernel). Specifically,we employ a correntropy-based mappingas kernel functionalto code higher-order statistics of the inputdata under both nonlinear and non-Gaussian conditions. We validate our approach againstan UI dataset focused on nerve segmentation for PNB. Likewise, our Correntropy-based Pre-Image Filtering (CPIF) is applied as a pre-processing stage to segment nerve structures in a UI. The segmentation performance is measured in terms of the Dice coefficient. According to the results, we observe that CPIF finds a suitable approximation for UI by highlighting discriminative nerve patterns.
Authors and Affiliations
J. Gil-González, A. Álvarez-Meza, M. Álvarez-López
Keywords
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- EP ID EP348408
- DOI 10.22430/22565337.717
- Views 117
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