Publications by authors named "Christian Scharfenberger"

Photoplethysmography (PPG) devices are widely used for monitoring cardiovascular function. However, these devices require skin contact, which restricts their use to at-rest short-term monitoring. Photoplethysmographic imaging (PPGI) has been recently proposed as a non-contact monitoring alternative by measuring blood pulse signals across a spatial region of interest.

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We propose a simple yet effective structure-guided statistical textural distinctiveness approach to salient region detection. Our method uses a multilayer approach to analyze the structural and textural characteristics of natural images as important features for salient region detection from a scale point of view. To represent the structural characteristics, we abstract the image using structured image elements and extract rotational-invariant neighborhood-based textural representations to characterize each element by an individual texture pattern.

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Rehabilitative Ultrasound Imaging or diagnostic ultrasound is used to measure geometric properties of the lumbar multifidus muscle to infer muscle strength or degeneration for back pain therapy. For this purpose, a novel semi-automatic approach (FTS: Fisher-Tippett Segmentation) based upon the Decoupled Active Contour is proposed to reliably and quickly segment the lumbar multifidus muscle in diagnostic ultrasound. To overcome speckle or hardly visible region boundaries in ultrasound images, we first propose a novel external energy functional to explicitly consider the underlying Fisher-Tippett distribution of ultrasound data.

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Active contours are a popular approach for object segmentation that uses an energy minimizing spline to extract an object's boundary. Nonparametric approaches can be computationally complex, whereas parametric approaches can be impacted by parameter sensitivity. A decoupled active contour (DAC) overcomes these problems by decoupling the external and internal energies and optimizing them separately.

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