Thomas R. Langerak

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PURPOSE Automatic, atlas-based segmentation of medical images benefits from using multiple atlases, mainly in terms of robustness. However, a large disadvantage of using multiple atlases is the large computation time that is involved in registering atlas images to the target image. This paper aims to reduce the computation load of multiatlas-based(More)
Deformable registration is prone to errors when it involves large and complex deformations, since the procedure can easily end up in a local minimum. To reduce the number of local minima, and thus the risk of misalignment, regularization terms based on prior knowledge can be incorporated in registration. We propose a regularization term that is based on(More)
Form feature modeling is a much used shape modeling technique that offers high-level control over a shape. When a feature-based interpretation of shape data is not available, e.g. when a shape is obtained by a laser range scanner or from a database of shapes, then the features must be reconstructed through feature recognition. Many methods for the(More)
Feature modeling has simplified, improved and accelerated the Computer-Aided Design (CAD) process. However, this modeling paradigm still has some serious shortcomings. Firstly, its domain is currently restricted to regular and simple freeform shapes. Secondly, most current feature modelers do not allow new class definitions, but instead provide design with(More)
Prototyping plays an important role in industrial product designs. In this paper, for achieving a more intuitive and interactive prototyping, a selective clay milling center is introduced based on a synthesis of clay modeling, 3Dimensional (3-D) scanning, robot machining and advanced geometric tools. In the system, the product shape design may start either(More)
Automated segmentation is required for radiotherapy treatment planning, and multi-atlas methods are frequently used for this purpose. The combination of multiple intermediate results from multi-atlas segmentation into a single segmentation map can be achieved by label fusion. A method that includes expert knowledge in the label fusion phase of(More)
In multi-atlas based segmentation, a target image is segmented by registering multiple atlas images to this target image and propagating the corresponding atlas segmentations. These propagated segmentations are then combined into a single segmentation in a process called label fusion. Multi-atlas based segmentation is a segmentation method that allows fully(More)