We introduce a framework for actively learning visual categories from a mixture of weakly and strongly labeled image examples. We propose to allow the categorylearner to strategic...
Fitting statistical models is a widely employed technique for the segmentation of medical images. While this approach gives impressive results for simple structures, shape models a...
Many current medical image analysis problems involve learning thousands or even millions of model parameters from extremely few samples. Employing sparse models provides an effecti...
Abstract. This work presents an approach towards reconstructing ligament and tendon attachment sites from 3D medical image data. We apply statistical shape models with an additiona...
Heiko Seim, Hans Lamecker, Markus Heller, Stefan Z...
The notion of using context information for solving high-level vision and medical image segmentation problems has been increasingly realized in the field. However, how to learn a...