Abstract. We present a model for complex documents possibly consisting of a hierarchically structured set of images or texts. Documents are represented both at the form level (as s...
Carlo Meghini, Fabrizio Sebastiani, Umberto Stracc...
We propose a new framework for multi-object segmentation of deep brain structures, which have significant shape variations and relatively small sizes in medical brain images. In th...
This paper presents a deformable model for automatically segmenting objects from volumetric MR images and obtaining point correspondences, using geometric and statistical informati...
In this paper, we present a learning-based method for the detection and segmentation of 3D free-form tubular structures, such as the rectal tubes in CT colonoscopy. This method can...
Most image retrieval systems perform a linear search over the database to find the closest match to a query. However, databases usually exhibit a natural grouping structure into c...