Sascha Seifert

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Automated segmentation of the esophagus in CT images is of high value to radiologists for oncological examinations of the mediastinum. It can serve as a guideline and prevent confusion with pathological tissue. However, segmentation is a challenging problem due to low contrast and versatile appearance of the esophagus. In this paper, a two step method is(More)
In this paper we propose a novel learning–based CBIR method for fast content–based retrieval of similar 3D images based on the intrinsic Random Forest (RF) similarity. Furthermore, we allow the combination of flexible user–defined semantics (in the form of retrieval contexts and high–level concepts) and appearance–based (low–level) features in order to(More)
Examinations of the spinal column with both, Magnetic Resonance (MR) imaging and Computed Tomography (CT), often require a precise three-dimensional positioning, angulation and labeling of the spinal disks and the vertebrae. A fully automatic and robust approach is a prerequisite for an automated scan alignment as well as for the segmentation and analysis(More)
For surgical planning in spine surgery, the segmentation of anatomical structures is a prerequisite. Past efforts focussed on the segmentation of vertebrae from tomographic data, but soft tissue structures have, for the most part, been neglected. Only sparse research work has been done for the spinal cord and the trachea. However, as far as the author is(More)
Being able to segment the esophagus without user interaction from 3-D CT data is of high value to radiologists during oncological examinations of the mediastinum. The segmentation can serve as a guideline and prevent confusion with pathological tissue. However, limited contrast to surrounding structures and versatile shape and appearance make segmentation a(More)
In this paper, a method is described to automatically estimate the visible body region of a computed tomography (CT) volume image. In order to quantify the body region, a body coordinate (BC) axis is used that runs in longitudinal direction. Its origin and unit length are patient-specific and depend on anatomical landmarks. The body region of a test volume(More)
We present a system that integrates ontology-based meta-data extraction from medical images with a state-of-the-art object recognition algorithm for 3D volume data sets generated by Computed To-mography scanners. Extracted metadata and automatically generated medical image annotations are stored as instances of OWL classes. This system is applied to a(More)
Introduction For preoperative surgical planning, a simulation system has to support realistic cuts, which are normally smooth and curved. Since biological soft tissue is deformed with large displacement on an incision, the soft tissue model should support nonlinearity. Although the focus of surgical planning is accuracy, good acceptance by the surgeons can(More)