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J J Jacq

Publications and source records attributed to J J Jacq.

2 recordsLinked to original sources

Genetic algorithms for a robust 3-D MR-CT registration.

The aim of this paper is to present an original usage of genetic algorithms as a robust search space sampler in application to 3-D medical image elastic registration. An overview of the standard steps of a registration algorithm is given. We focus on the genetic algorithms use and particularly on the problem of extraction of the optimal solution among the final genetic population. We provide an original encoding scheme relying on a structural approach of point matching and then point out the need for a local optimization process. We then illustrate the algorithm with a concrete registration example and assert the results with a direct multivolume rendering tool. Finally, the algorithm is applied on the vanderbilt medical image database to assert the robustness and in order to compare it with other techniques.

Algorithms↗

A direct multi-volume rendering method aiming at comparisons of 3-D images and models.

We present a new method for direct volume rendering of multiple three-dimensional (3-D) functions using a density emitter model. This work aims at obtaining visual assessment of the results of a 3-D image registration algorithm which operates on anisotropic and non segmented medical data. We first discuss the fundamentals associated with direct, simultaneous rendering of such datasets. Then, we recall the fuzzy classification and fuzzy surface rendering theory within the density emitter model terminology, and propose an extension of standard direct volume rendering that can handle the rendering of two or more 3-D functions; this consists of the definition of merging rules that are applied on emitter clouds. The included rendering applications are related on one hand, to volume-to-volume registration, and on the other hand, to surface-to-volume registration: the first case is concerned with global elastic registration of CT data, and the second one presents fitting of an implicit surface over a CT data subset. In these two medical imaging application cases, our rendering scheme offers a comprehensive appreciation of the relative position of structural information.

Algorithms↗