28 citations · 49 across the 6 of their papers we have counts for
6 papers
Voreen -- An Open-source Framework for Interactive Visualization and Processing of Large Volume Data
Dominik Drees, Simon Leistikow, Xiaoyi Jiang +1
Technological advances for measuring or simulating volume data have led to large data sizes in many research areas such as biology, medicine, physics, and geoscience. Here, large d…
A Bhattacharyya Coefficient-Based Framework for Noise Model-Aware Random Walker Image Segmentation
Dominik Drees, Florian Eilers, Ang Bian +1
One well established method of interactive image segmentation is the random walker algorithm. Considerable research on this family of segmentation methods has been continuously con…
A Streaming Volumetric Image Generation Framework for Development and Evaluation of Out-of-Core Methods
Dominik Drees, Xiaoyi Jiang
Advances in 3D imaging technology in recent years have allowed for increasingly high resolution volumetric images of large specimen. The resulting datasets of hundreds of Gigabytes…
Hierarchical Random Walker Segmentation for Large Volumetric Biomedical Images
Dominik Drees, Florian Eilers, Xiaoyi Jiang
The random walker method for image segmentation is a popular tool for semi-automatic image segmentation, especially in the biomedical field. However, its linear asymptotic run time…
Scalable Robust Graph and Feature Extraction for Arbitrary Vessel Networks in Large Volumetric Datasets
Dominik Drees, Aaron Scherzinger, René Hägerling +2
Recent advances in 3D imaging technologies provide novel insights to researchers and reveal finer and more detail of examined specimen, especially in the biomedical domain, but als…
Barista - a Graphical Tool for Designing and Training Deep Neural Networks
Soeren Klemm, Aaron Scherzinger, Dominik Drees +1
In recent years, the importance of deep learning has significantly increased in pattern recognition, computer vision, and artificial intelligence research, as well as in industry.…