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Rapport Année : 1997

Deformation Analysis to Detect and Quantify Active Lesions in 3D Medical Image Sequences

Résumé

Evaluating precisely the temporal variations of tumor volumes is very important for at least three types of practical applications: pharmaceutical trials, decision making for drug treatment or surgery and patients follow-up. In this paper, we present a volumetric analysis technique, combining precise rigid registration of 3D medical images, non-rigid deformation computation and flow field analysis. Our analysis technique has two outcomes: the detection of evolving lesions and the quantitative measurement of volume variations. The originality of our approach is that no precise} segmentation of the lesion is needed but the approximative designation of a region of interest, which can be automatized. We distinguish between tissue transformation (image intensity changes without deformation) and expansion or contraction effects reflecting a change of mass within the tissue; a real lesion being generally the combination of both effects. The method is tested with synthesized 3D image sequences and applied, in a first attempt to quantify in-vivo a mass effect, to the analysis of a real patient case with Multiple Sclerosis.
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Dates et versions

inria-00073590 , version 1 (24-05-2006)

Identifiants

  • HAL Id : inria-00073590 , version 1

Citer

Jean-Philippe Thirion, Guillaume Calmon. Deformation Analysis to Detect and Quantify Active Lesions in 3D Medical Image Sequences. RR-3101, INRIA. 1997. ⟨inria-00073590⟩
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