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This paper proposes a model-based methodology for recognizing and tracking objects in digital image sequences. Objects are represented by attributed relational graphs (or ARGs), which carry both local and relational information about them. The recognition is performed by inexact graph matching, which consists in finding an approximate homomorphism between ARGs derived from an input video and a model...
This paper deals with the problem of non-linear landmark-based registration of CT (at two different instants of the breathing cycle, intermediate expirations) and PET images of thoracic regions. We propose a general method to introduce a breathing model in a registration procedure in order to simulate the instant in the breathing cycle most similar to the PET image and guarantee physiologically plausible...
Complex multimedia medical information is being increasingly used to enable diagnosis. Despite the recognized potential of emerging exploitation of such medical information, known electronic patient record applications do not offer the possibility to make use of them. In order to examine the interest of handling complementary medical information, this work focuses on the integration into the electronic...
A two-level approach for modeling and fusion of antipersonnel mine detection sensors in terms of belief functions within the Dempster-Shafer framework is presented. Three promising and complementary sensors are considered: a metal detector, an infrared camera, and a ground-penetrating radar. Since the metal detector, the most often used mine detection sensor, provides measures that have different...
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