Computergrafik und Bildverarbeitung

Nischwitz, Alfred; Fischer, Max; Haberäcker, Peter; Socher, Gudrun

doi:10.1007/978-3-8348-8323-0

Cited by 5 publications

(7 citation statements)

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“…In the following step, skeletonization of the foreground regions is performed according to Euler characteristics [30]. The obtained skeleton is pruned by deleting short branches that are attached to the main skeleton line.…”

Section: Resultsmentioning

confidence: 99%

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Toponomics method for the automated quantification of membrane protein translocation

et al. 2011

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BackgroundIntra-cellular and inter-cellular protein translocation can be observed by microscopic imaging of tissue sections prepared immunohistochemically. A manual densitometric analysis is time-consuming, subjective and error-prone. An automated quantification is faster, more reproducible, and should yield results comparable to manual evaluation. The automated method presented here was developed on rat liver tissue sections to study the translocation of bile salt transport proteins in hepatocytes. For validation, the cholestatic liver state was compared to the normal biological state.ResultsAn automated quantification method was developed to analyze the translocation of membrane proteins and evaluated in comparison to an established manual method. Firstly, regions of interest (membrane fragments) are identified in confocal microscopy images. Further, densitometric intensity profiles are extracted orthogonally to membrane fragments, following the direction from the plasma membrane to cytoplasm. Finally, several different quantitative descriptors were derived from the densitometric profiles and were compared regarding their statistical significance with respect to the transport protein distribution. Stable performance, robustness and reproducibility were tested using several independent experimental datasets. A fully automated workflow for the information extraction and statistical evaluation has been developed and produces robust results.ConclusionsNew descriptors for the intensity distribution profiles were found to be more discriminative, i.e. more significant, than those used in previous research publications for the translocation quantification. The slow manual calculation can be substituted by the fast and unbiased automated method.

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Section: Resultsmentioning

confidence: 99%

“…where e is the number of corners, k defines the number of edges, and f is the number of faces [30]. An image was scanned with 3 × 3 pixel window and an Euler characteristic was calculated.…”

Section: Methodsmentioning

confidence: 99%

Toponomics method for the automated quantification of membrane protein translocation

et al. 2011

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“…Die wahren Helligkeiten b(x, y) der Bildpunkte in der zu untersuchenden Bildszene lassen sich dann aus den aufgenommenen Grauwerten g(x, y) mittels Division durch die Referenzgrauwerte und Multiplikation mit der Referenzhelligkeit b berechnen, (Nischwitz et al 2007): Es entsteht ein Bild mit den Referenzgrauwerten g r (x, y), aus denen sich bei bekannter Helligkeit b der aufgenommenen Fläche die Korrekturwerte zu f(x, y) = g r (x, y)/b ergeben.…”

Section: Originalbildunclassified

“…B. auch in(Parker 1994),(Nischwitz 2007),(Gonzalez und Woods 2008) und (Sonka et al 2008) verwendet wird. B. auch in(Parker 1994),(Nischwitz 2007),(Gonzalez und Woods 2008) und (Sonka et al 2008) verwendet wird.…”

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Industrielle Bildverarbeitung

Demant¹,

Streicher-Abel²,

Springhoff³

2011

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“…For this step there is no z-coordinate (the up vector in our coordinate system), so the backface culling [1] method is reduced to a 2-dimensional problem.…”

Section: Backface Cullingmentioning

confidence: 99%

Evaluation of Pose Hypotheses by Image Feature Extraction for Vehicle Localization

Schönherr

Giesler

Knoll³

2010

Artificial Intelligence and Soft Computing

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Abstract. For the realization of driving assistance and safety systems vehicles are being increasingly equipped with sensors. As these sensors contribute a lot to the cost of the whole package and at the same time consume some space, car manufacturers try to integrate applications that make use of already integrated sensors. This leads to the fact that each sensor has to fulfil several functions at once and to deliver information to different applications. When estimating very precise positioning information of a vehicle existing sensors have to be combined in an appropriate way to avoid the integration of additional sensors into the vehicle. The GPS receiver, which is coupled with the navigation assistant of the vehicle, delivers a rough positioning information, which has to be improved using already available information from other built in sensors. The approach discussed in this paper uses a model-based method to compare building models obtained from maps with video image information. We will examine, if the explorative coupling of sensors can deliver an appropriate evaluation criteria for positioning hypotheses.

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Computergrafik und Bildverarbeitung

Cited by 5 publications

References 0 publications

Toponomics method for the automated quantification of membrane protein translocation

Toponomics method for the automated quantification of membrane protein translocation

Industrielle Bildverarbeitung

Evaluation of Pose Hypotheses by Image Feature Extraction for Vehicle Localization

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