Method for the evaluation of the thickness of a tissue of an organ
A computer-implemented method for the evaluation of an adjusted thickness of a tissue of an organ, the method comprising: step (1) of receiving at least one mapping of points ( 10 ) representing said tissue, said mapping of points ( 10 ) defining an inner border ( 102 ) and an outer border ( 101 ) of said tissue; step (2) of segmentation of the mapping of points ( 10 ) by classification of each point ( 11 ) from the mapping of points ( 10 ) into a class belonging to a set of different classes; step (3) of determining a plurality of trajectories ( 109 ) each joining one point ( 108 ) of the inner border ( 102 ) to one point ( 107 ) of the outer border ( 101 ); step (4) of computing for each trajectory ( 109 ) the value of a thickness function depends on said trajectory ( 109 ) and the classes assigned to the points of the mapping of points ( 10 ) through which said trajectory encompasses; and step (5) of generation of a 3D model ( 1000 ) of said tissue from said mapping of points ( 10 ), wherein at least to each voxel of said 3D model ( 1000 ) corresponding to the inner border ( 102 ) and/or to the outer border ( 101 ) of said tissue is assigned an adjusted thickness value determined from the value of the thickness function associated to the trajectory encompassing said voxels.
1 . A computer-implemented method for the evaluation of an adjusted thickness of a tissue of an organ, the method comprising:
a. step (1) of receiving at least one mapping of points ( 10 ) representing said tissue, said mapping of points ( 10 ) defining an inner border ( 102 ) and an outer border ( 101 ) of said tissue;
b. step (2) of segmentation of the mapping of points ( 10 ) by classification of each point ( 11 ) from the mapping of points ( 10 ) into a class belonging to a set of different classes;
c. step (3) of determining a plurality of trajectories each joining one point ( 108 ) of the inner border ( 102 ) to one point ( 107 ) of the outer border ( 101 );
d. step (4) of computing for each trajectory ( 109 ) the value of a thickness function, wherein said thickness function depends on said trajectory ( 109 ) and the classes assigned to the points of the mapping of points ( 10 ) through which said trajectory ( 109 ) encompasses, wherein the thickness function value is computed from a value of arclength of said trajectory ( 109 ) weighted with coefficients depending on the classes by instantiating the arclength function value to 0 and traversing a set of points of the mapping of points by recursively computing a new value of said arclength value for each new traversed point, said new value being computed from the previous value of said thickness function value and from the class assigned to said new traversed point; and
e. step (5) of generation of a 3D model ( 1000 ) of said tissue from said mapping of points ( 10 ), wherein at least to one voxel of said 3D model ( 1000 ) is assigned an adjusted thickness value determined from the value of the thickness function associated to the trajectory ( 109 ) encompassing said voxel.
2 . The method according to claim 1 , wherein to each point ( 11 ) of the mapping of points ( 10 ) which is received is associated at least one value depending on the type of the tissue at a location corresponding to said point ( 11 ), and wherein the step (2) of segmentation is implemented by associating a class selected from the set of classes from said value associated to said point ( 11 ) of the mapping of points ( 10 ).
3 . The method according to claim 1 , wherein the segmentation classes comprise at least one class among muscle tissue ( 103 , 104 ), fat tissue ( 105 ) or calcified tissue ( 106 ).
4 . The method according to claim 1 , wherein the plurality of trajectories is defined from a vector field ( 110 ) pointing from the inner border ( 102 ) to the outer border ( 101 ).
5 . The method according to claim 1 , wherein said new value is computed from the previous value of said thickness function value incremented by a factor whose value depends on the class assigned to said new traversed point.
6 . The method according to claim 5 , wherein said factor value is a non-null step value when the class assigned to said new traversed point is a predetermined class and 0 otherwise.
7 . The method according to claim 5 , wherein said factor value depends on the number of points to which said predetermined class is assigned among a set of points included into a bounding region centered on said new traversed point.
8 . The method according to claim 1 , wherein to at least to each voxel of said 3D model ( 1000 ) corresponding to the inner border ( 102 ) and/or to the outer border ( 101 ) of said tissue is assigned an adjusted thickness value determined from the value of the thickness function associated to the trajectory ( 109 ) encompassing said voxels.
9 . The method according to claim 8 , wherein to each voxel of said 3D model ( 1000 ) corresponding to the inner border ( 102 ) and/or to the outer border ( 101 ) of said tissue is assigned a color determined from the adjusted thickness value assigned to this voxel, said color being selected from a set of colors each associated to a thickness range.
10 . The method according to claim 1 , wherein said generated 3D model ( 1000 ) of said tissue comprises a plurality of sub-meshes, and wherein each sub-mesh is associated to a predetermined thickness range and comprises each voxel of said 3D model whose adjusted thickness value assigned to this voxel belongs to this predetermined thickness range.