PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Di Bona S., Salvetti O. An efficient method to map a regular mesh into a 3D neural network. In: ICIP 2001- Internal Conference on Image (Thessaloniki, Greece, 7-10 October 2001). Proceedings, pp. 529 - 532. IEEE, 2001.
 
 
Abstract
(English)
In 3D computer vision a relevant problem is to match a "source" image dataset with a "target" image dataset. The matching problem can be faced using a neural net approach, where the nodes are related with the image voxels and the synapses to the voxel information. This paper presents an improvement of the "Volume-Matcher" project, n approach to the data-driver and registration of three-dimensional images based on 3D neural networks. The approach has been improved by introducing a method for an efficient mapping of a regular mesh into a 3D neural network in order to reduce the computational complexity. The algorithms developed have been tested on real cases of interest in the field of medical imaging.
Subject 3D neural netwok
3D computer vision
I.4.10 Image Representation: Volumetric


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