Hierarchical Learning of Curves Application to Guidewire Localization in Fluoroscopy

In this paper we present a method for learning a curve model for detection and segmentation by closely integrating a hierarchical curve representation using generative and discriminative models with a hierarchical inference algorithm. We apply this method to the problem of automatic localization of the guidewire in fluoroscopic sequences. In fluoroscopic sequences, the guidewire appears as a hardly visible, non-rigid one-dimensional curve. Our paper has three main contributions. Firstly, we present a novel method to learn the complex shape and appearance of a free-form curve using a hierarchical model of curves of increasing degrees of complexity and a database of manual annotations. Secondly, we present a novel computational paradigm in the context of Marginal Space Learning, in which the algorithm is closely integrated with the hierarchical representation to obtain fast parameter inference. Thirdly, to our knowledge this is the first full system which robustly localizes the whole gu...

• Type: Conference
• Year: 2007
• Where: CVPR
• Authors: Adrian Barbu, Vassilis Athitsos, Bogdan Georgescu, Stefan Böhm, Peter Durlak, Dorin Comaniciu
• Keywords: Computer Vision, CVPR 2007, Free-form Curve, Hierarchical Curve Representation, Hierarchical Inference Algorithm, Hierarchical Representation, Non-rigid One-dimensional Curve