@article {853,
	title = {Hierarchical Image Semantics using Probabilistic Path Propagations for Biomedical Research},
	journal = {IEEE computer graphics and applications},
	volume = {39},
	year = {2019},
	abstract = {Image segmentation is an important subtask in biomedical research applications, such as estimating the position and shape of a tumor. Unfortunately, advanced image segmentation methods are not widely applied in research applications as they often miss features, such as uncertainty communication, and may lack an intuitive approach for the use of the underlying algorithm. To solve this problem, this paper fuses a fuzzy and a hierarchical segmentation approach together, thus providing a flexible multiclass segmentation method based on probabilistic path propagations. By utilizing this method, analysts and physicians can map their mental model of image components and their composition to higher level objects. The probabilistic segmentation of higher order components is propagated along the user-defined hierarchy to highlight the potential of improvement resulting in each level of hierarchy by providing an intuitive representation. The effectiveness of this approach is
demonstrated by evaluating our segmentations of biomedical datasets, comparing it to the state-of-the-art segmentation approaches, and an extensive user study.},
	author = {Gillmann, Christina and Post, Tobias and Wischgoll, Thomas and Hagen, Hans and Maciejewski, Ross}
}
@article {858,
	title = {An uncertainty-aware workflow for keyhole surgery planning using hierarchical image semantics},
	journal = {Visual Informatics},
	volume = {2},
	year = {2018},
	abstract = {Keyhole surgeries become increasingly important in clinical daily routine as they help minimizing the damage of a patient{\textquoteright}s healthy tissue. The planning of keyhole surgeries is based on medical imaging and an important factor that influences the surgeries{\textquoteright} success. Due to the image reconstruction process, medical image data contains uncertainty that exacerbates the planning of a keyhole surgery. In this paper we present a visual workflow that helps clinicians to examine and compare different surgery paths as well as visualizing the patients{\textquoteright} affected tissue. The analysis is based on the concept of hierarchical image semantics, that segment the underlying image data with respect to the input images{\textquoteright} uncertainty and the users understanding of tissue composition. Users can define arbitrary surgery paths that they need to investigate further. The defined paths can be queried by a rating function to identify paths that fulfill user-defined properties. The workflow allows a visual inspection of the affected tissues and its substructures. Therefore, the workflow includes a linked view system indicating the three-dimensional location of selected surgery paths as well as how these paths affect the patients tissue. To show the effectiveness of the presented approach, we applied it to the planning of a keyhole surgery of a brain tumor removal and a kneecap surgery.},
	author = {Gillmann, Christina and Maack, Robin and Post, Tobias and Wischgoll, Thomas and Hagen, Hans}
}
@conference {860,
	title = {Visual Analytics of Cascaded Bottlenecks in Planar Flow Networks},
	booktitle = {LEVIA 2018},
	year = {2018},
	abstract = {
Finding bottlenecks and eliminating them to increase the overall flow of a network often appears in real world applications, such as production planning, factory layout, flow related physical approaches, and even cyber security. In many cases, several edges can form a bottleneck (cascaded bottlenecks). This work presents a visual analytics methodology to analyze these cascaded bottlenecks. The methodology consists of multiple steps: identification of bottlenecks, identification of potential improvements, communication of bottlenecks, interactive adaption of bottlenecks, and a feedback loop that allows users to adapt flow networks and their resulting bottlenecks until they are satisfied with the flow network configuration. To achieve this, the definition of a minimal cut is extended to identify network edges that form a (cascaded) bottleneck. To show the effectiveness of the presented approach, we applied the methodology to two flow network setups and show how the overall flow of these networks can be improved.},
	author = {Post, Tobias and Gillmann, Christina and Wischgoll, Thomas and Hamann, Bernd and Hagen, Hans}
}
@article {861,
	title = {An Industrial Vision System to Analyze the Wear of Cutting Tools},
	journal = {Applied Mechanics and Materials},
	volume = {869},
	year = {2017},
	abstract = {The wear behavior of cutting tools directly affects the quality of the machined part. The measurement and evaluation of wear is a time consuming and process and is subjective. Therefore, an image-based wear measure that can be computed automatically based on given image series of cutting tools and an objective way to review the resulting wear is presented in this paper. The presented method follows the industrial vision system pipeline where images of cutting tools are used as input which are then transformed through suitable image processing methods to prepare them for the computation of a novel image based wear measure. For multiple cutting tool settings a comparative visualization of the wear measure outputs is presented. The effectiveness of the presented approach is shown by applying the method to measure the wear of four different cutting tool shapes.},
	author = {Gillmann, Christina and Post, Tobias and Kirsch, Benjamin and Wischgoll, Thomas and J{\"o}rg, Hartig and Hamann, Bernd and Hagen, Hans and Aurich, Christian}
}
@conference {864,
	title = {Fast 3D Thinning of Medical Image Data based on Local Neighborhood Lookups},
	booktitle = {EuroVis (Short Papers)},
	year = {2016},
	abstract = {Three-dimensional thinning is an important task in medical image processing when performing quantitative analysis on structures, such as bones and vessels. For researchers of this domain a fast, robust and easy to access implementation is required.
The Insight Segmentation and Registration Toolkit (ITK) is often used in medical image processing and visualization as it offers
a wide range of ready to use algorithms. Unfortunately, its thinning implementation is computationally expensive and can introduce errors in the thinning process. This paper presents an implementation that is ready to use for thinning of medical image
data. The implemented algorithm evaluates a moving local neighborhood window to find deletable voxels in the medical image.
To reduce the computational effort, all possible combinations of a local neighborhood are stored in a precomputed lookup table.
To show the effectiveness of this approach, the presented implementation is compared to the performance of the ITK library.},
	author = {Post, Tobias and Gillmann, Christina and Wischgoll, Thomas and Hagen, Hans}
}
@conference {866,
	title = {OpenThinning: Fast 3D Thinning based on Local Neighborhood Lookups},
	booktitle = {Vis in Practice 2016},
	year = {2016},
	abstract = {3D Thinning is an often required image processing task in order to perform shape analysis in various applications. For researchers in these domains, a fast, flexible and easy to access implementation is required. Open source solutions, as the Insights Segmentation and Registration Toolkit (ITK), are often used for image processing and visualization tasks, due to their wide range of provided algorithms. Unfortunately, ITK{\textquoteright}s thinning implementation is computational expensive and allows solely one specific thinning approach. Therefore, this work presents OpenThinning, an open source thinning solution for 3D image data. The implemented algorithm evaluates a moving local neighborhood to find deletable voxels, according to different sets of criteria. In order to reduce the computational effort, all possible local neighborhood setting outputs are stored in a lookup table. To show the effectiveness of OpenThinning, the implementation is compared to the performance of the ITK library.},
	author = {Post, Tobias and Gillmann, Christina and Wischgoll, Thomas and Hagen, Hans}
}
