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

Jean-Philippe Thirion 1 Guillaume Calmon
1 EPIDAURE - Medical imaging and robotics
CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : 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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https://hal.inria.fr/inria-00073590
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Submitted on : Wednesday, May 24, 2006 - 1:16:23 PM
Last modification on : Friday, February 4, 2022 - 3:16:30 AM
Long-term archiving on: : Sunday, April 4, 2010 - 11:51:10 PM

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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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