Image processing method for estimating a risk of atheroma plaque breakage
The invention relates to an image processing method for estimating a risk of atheroma plaque breakage, that includes the step of receiving ( 40 ) a so-called elastogram image representing the inner deformation resulting from the compression of an analyzed blood vessel tissue based on blood pressure, the step of pre-segmenting ( 50 ) the elastogram in order to obtain a pre-segmented image including a plurality of areas, and the step of calculating an elasticity image ( 60 ) representing the elasticity of at least one region of the elastogram, the region corresponding to an area selected among the plurality of areas of the pre-segmented image, and the elasticity image enabling the user to estimate the risk of atheroma plaque breakage, wherein said method is characterized in that: the pre-segmentation is carried out while considering the tissue as being a non-compressible elastic solid in order to determine the Young modulus gradient as equal to the sum of the Lagrange multiplier gradient and of a space depending vector, and in that the pre-segmentation includes determining the outlines of each area in the plurality of areas using said space depending vector.
1. An image processing method for estimating risk of rupture of an atheromatous plaque, comprising:
a step of receiving an image called an “elastogram” depicting internal deformations resulting from compression of a blood vessel tissue analyzed as function of blood pressure,
a pre-segmentation step of the elastogram to obtain a pre-segmented image comprising a plurality of zones, and
a computing step of an elasticity image showing the elasticity of at least one region in the elastogram, the region corresponding to a zone selected from among the plurality of zones of the pre-segmented image, and the elasticity image enabling the user to estimate the risk of rupture of an atheromatous plaque,
a method wherein:
first, the pre-segmentation step is performed considering the tissue to be an incompressible elastic solid so as to determine the gradient of Young's modulus as being equal to the sum of the gradient of the Lagrange multiplier and a space-dependent vector of the form H=−[ε] −1 div [ε], where [ε] is the deformation matrix, [ε] −1 the inverse of the deformation matrix, and div [ε] is the divergence of the deformation matrix,
second, the pre-segmentation step comprises the determination of the contours of each zone of the plurality of zones by means of said space-dependent vector.
2. The method according to claim 1 , wherein the contours of each zone of the plurality of zones correspond to the maximum values of the space-dependent vector.
3. The method according to claim 1 , wherein the computing step of an elasticity image comprises a sub-step of watershed segmentation wherein the zones are successively selected from among the plurality of zones of the pre-segmented image.
4. The method according to claim 3 , wherein the zones are successively selected from the zone of the pre-segmented image with highest intensity for H to the zone of the pre-segmented image with lowest intensity for H.
5. The method according to claim 3 , wherein the computing step of the elasticity image also comprises a an optimization sub-step performed after selection of each new zone n+1 at the segmentation step.
6. The method according to claim 5 , wherein at the optimization step, the elasticity of the new zone n+1 selected at the segmentation step is estimated by minimizing an error, called a strain error, between the measured strains of the elastogram and the computed strains of the n+1 selected zones.
7. The method according to claim 3 , wherein the computing step of the elasticity image comprises a comparison step of the elasticity image with a criterion for stopping the computing step of the elasticity image.
8. The method according to claim 7 wherein the stop criterion is that the difference between two strain errors computed during two successive steps characterizing the elasticities of the n and n+1 zones is lower than 10 −7 .
9. The method according to claim 7 , wherein the stop criterion is that the number of selected zones is greater than 10.
10. An image processing system for estimating risk of atheromatous plaque rupture, the system implementing the method according to claim 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 or 9 .
11. A non-transitory computer readable medium comprising program code instructions for implementing the method according to claim 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 or 9 .