Impact of Physical Noise Modeling on Image Segmentation in Echocardiography

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dc.contributor.authorTenbrinck, Danielen_US
dc.contributor.authorSawatzky, Alexen_US
dc.contributor.authorJiang, Xiaoyien_US
dc.contributor.authorBurger, Martinen_US
dc.contributor.authorHaffner, Wladimiren_US
dc.contributor.authorWillems, Patricken_US
dc.contributor.authorPaul, Matthiasen_US
dc.contributor.authorStypmann, Jörgen_US
dc.contributor.editorTimo Ropinski and Anders Ynnerman and Charl Botha and Jos Roerdinken_US
dc.date.accessioned2013-11-08T10:34:15Z
dc.date.available2013-11-08T10:34:15Z
dc.date.issued2012en_US
dc.description.abstractSegmentation is an essential task in ultrasound image analysis. Recently, the trend in literature is towards incorporation of high-level information, e.g., shape priors, since many low-level segmentation techniques suffer from the characteristics of medical ultrasound images, i.e., speckle noise, scattering artifacts, and shadowing effects. However, the majority of these works implicitly assume an additive Gaussian noise model in ultrasound images, although a strong deviation from this assumption is well known, and the impact of correct physical noise modeling is not examined sufficiently until now. In this paper we investigate the influence of three different noise models from literature using a variational region-based segmentation framework, which allows for the incorporation of both low-level and high-level information. We demonstrate that correct physical noise modeling is of high importance for the computation of accurate segmentation results. The numerical results are validated on real patient datasets from echocardiographic examinations and compared to manual segmentations from echocardiographic experts.en_US
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biology and Medicineen_US
dc.identifier.isbn978-3-905674-38-5en_US
dc.identifier.issn2070-5778en_US
dc.identifier.urihttps://doi.org/10.2312/VCBM/VCBM12/033-040en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.4.6 [Image Processing and Computer Vision]en_US
dc.subjectSegmentationen_US
dc.subjectRegion growingen_US
dc.subjectpartitioningen_US
dc.subjectI.4.7 [Image Processing and Computer Vision]en_US
dc.subjectFeature Measurementen_US
dc.subjectMomentsen_US
dc.titleImpact of Physical Noise Modeling on Image Segmentation in Echocardiographyen_US
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VCBM 12: Eurographics Workshop on Visual Computing for Biology and Medicine