Fast geometric flows based white matter fiber tract segmentation in DT-MRI
AssigneeSiemens Medical Solutions USA, Inc.
InventorsWeihong Guo, Zhizhou Wang
Life of this patent
Estimating the term…
Abstract
Segmentation of White Matter Fiber Tract in DT-MRI images is achieved by using level sets methods including a method which will increase the speed and quality of the surface evolvement. A method system representing a measure of coincidence of the tensor field with the normal of the surface front to increase the speed and quality of a level set method in DT-MRI is disclosed.
Claims12
A method to segment white matter fiber tracts from MRI image data by diffusion tensor imaging wherein a surface of an object is evolved using a surface evolution velocity, comprising:
- a processor to perform the following steps:
- determining the surface evolution velocity as a function of a normalized tensor scalar product plus a coincidence term that measures the coincidence of a normal direction and a tensor field;
- and
- growing the object in accordance with the surface evolution velocity;
- wherein the surface evolution velocity is expressed
- as F=mean(NTSP (Di, Di+1), NTSP(Di, Di+2))+βCOIN wherein:
- NTSP
-
- (
- D
- i
- ,
- D
- i
- -
- 1
- )
- =
- D
- i
- :
- D
- i
- -
- 1
- Trace
-
- (
- D
- i
- )
-
- Trace
-
- (
- D
- i
- -
- 1
- )
- ,
- wherein Di is the diffusion tensor;
- NTSP (Di, Di−1) is the normalized tensor scalar product;
- COIN is the coincidence factor and β is a constant.
A system to process an image from image data, including:
- a processor;
- application software operable on the processor to segment white matter fiber tracts from MRI image data by diffusion tensor imaging wherein a surface of an object is evolved using a surface evolution velocity, comprising:
- determining the surface evolution velocity as a function of a normalized tensor scalar product plus a coincidence term that measures the coincidence of a normal direction and a tensor field;
- and
- growing the object in accordance with the surface evolution velocity;
- wherein the surface evolution velocity is expressed
- as F=mean(NTSP (Di, Di+1), NTSP (Di, Di+2))+βCOIN wherein:
- NTSP
-
- (
- D
- i
- ,
- D
- i
- -
- 1
- )
- =
- D
- i
- :
- D
- i
- -
- 1
- Trace
-
- (
- D
- i
- )
-
- Trace
-
- (
- D
- i
- -
- 1
- )
- ,
- wherein Di is the diffusion tensor;
- NTSP (Di, Di−1) is the normalized tensor scalar product;
- COIN is the coincidence factor and β is a constant.
Dependencies are inferred from the claim text.