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1. (WO2019009954) CARTES PHYSIOLOGIQUES OBTENUES À PARTIR DE DONNÉES DE RADIOLOGIE MULTIPARAMÉTRIQUES
Note: Texte fondé sur des processus automatiques de reconnaissance optique de caractères. Seule la version PDF a une valeur juridique

CLAIMS:

1. A method for generating a physiology labeled image, comprising:

acquiring two or more multi-parametric images of a subject, wherein the two or more multi-parametric images are acquired using different imaging protocols;

performing a data reduction analysis on the two or more multi-parametric images, wherein the outputs of the data reduction analysis comprises computational products of the two or more images into one or more physiological components;

generating the physiology labeled image based on the computational products; and displaying the physiology labeled image for review.

2. The method of claim 1, wherein the multi-parametric images are acquired using one of a magnetic resonance imaging (MRI) system; a computed tomography (CT) imaging system, an ultrasound imaging system, a positron emission tomography (PET) imaging system, or a single photon emission computed tomography (SPECT) imaging system.

3. The method of claim 1 wherein the multi-parametric images are acquired using a magnetic resonance imaging (MRI) system and comprise one or more of T2 weighted (T2W) images, Tl weighted (TIW) images, diffusion weighted images (DWI), apparent diffusion coefficient (ADC) images, TIW post-contrast images, and fluid attenuated inversion recovery (FLAIR) images.

4. The method of claim 1, wherein the two or more multi-parametric images contain redundant or complementary information with respect to a physiological structure or function of interest.

5. The method of claim 1, wherein the physiology labeled image comprises one or more of an edema image, a necrosis image, an inflamed tissue image, an infarcted tissue image, or a cellularity image.

6. The method of claim 1, wherein the data reduction analysis comprises one or more of principal component analysis (PCA), independent component analysis (ICA), non-negative matrix factorization (NNMF), or convex analysis of mixtures with non-negative sources (CAMNS).

7. The method of claim 1, wherein the computational products comprise one or both of weight matrices and basis source vectors for the one or more physiological components.

8. The method of claim 1, wherein the computational products correspond to a signature of the one or more physiological components.

9. An image processing system, comprising:

a processor configured to execute executable instructions; and

a memory configured to store executable instructions that, when executed by the processor, cause act to be performed comprising:

acquiring or accessing two or more multi-parametric images of a subject, wherein the two or more multi-parametric images are acquired using different imaging protocols;

performing a data reduction analysis on the two or more multi-parametric images, wherein the outputs of the data reduction analysis comprises computational products of the two or more images into one or more physiological components; generating a physiology labeled image based on the computational products; and

displaying the physiology labeled image for review.

10. The image processing system of claim 9, wherein the multi-parametric images are acquired using one of a magnetic resonance imaging (MRI) system; a computed tomography (CT) imaging system, an ultrasound imaging system, a positron emission

tomography (PET) imaging system, or a single photon emission computed tomography (SPECT) imaging system.

11. The image processing system of claim 9, wherein the two or more multi-parametric images contain redundant or complementary information with respect to a physiological structure or function of interest.

12. The image processing system of claim 9, wherein the physiology labeled image comprises one or more of an edema image, a necrosis image, an inflamed tissue image, an infarcted tissue image, or a cellularity image.

13. The image processing system of claim 9, wherein the data reduction analysis comprises one or more of principal component analysis (PC A), independent component analysis (ICA), non-negative matrix factorization (NNMF), or convex analysis of mixtures with non-negative sources (CAMNS).

14. The image processing system of claim 9, wherein the computational products comprise one or both of weight matrices and basis source vectors for the one or more physiological components.

15. The image processing system of claim 9, wherein the computational products correspond to a signature of the one or more physiological components.

16. One or more non-transitory computer readable media encoding routines which, when executed, cause acts to be performed comprising:

acquiring two or more multi-parametric images of a subject, wherein the two or more multi-parametric images are acquired using different imaging protocols;

performing a data reduction analysis on the two or more multi-parametric images, wherein the outputs of the data reduction analysis comprises computational products of the two or more images into one or more physiological components;

generating a physiology labeled image based on the computational products; and displaying the physiology labeled image for review.

17. The one or more non-transitory computer readable media of claim 16, wherein the physiology labeled image comprises one or more of an edema image, a necrosis image, an inflamed tissue image, an infarcted tissue image, or a cellularity image.

18. The one or more non-transitory computer readable media of claim 16, wherein the data reduction analysis comprises one or more of principal component analysis (PCA), independent component analysis (ICA), non-negative matrix factorization (NNMF), or convex analysis of mixtures with non-negative sources (CAMNS).

19. The one or more non-transitory computer readable media of claim 16, wherein the computational products comprise one or both of weight matrices and basis source vectors for the one or more physiological components.

20. The one or more non-transitory computer readable media of claim 16, wherein the computational products correspond to a signature of the one or more physiological components.