METHOD, APPARATUS, COMPUTER-READABLE MEDIUM AND USE FOR PHARMACOKINETIC MODELING

• US 20100201686A1
• Filed: 08/03/2007
• Published: 08/12/2010
• Est. Priority Date: 08/02/2007
• Status: Abandoned Application

• Current Assignee: Koninklijke Philips N.V.
• Original Assignee: Koninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
• Inventors: Spies, Lothar, Paulus, Timo, Fischer, Alexander
• Application Number:
  US12/671,244
• Publication Number:
  US 20100201686A1
• Time in Patent Office: Days
• US Class Current: 345/424
• CPC Class Codes: H04L 51/214 using selective forwarding

Abstract

Methods and systems for interworking in messaging systems are described. An event store can be accessible by different dispatchers associated with different message servers. The dispatchers may be co-located with the event store or non co-located with the event store.

Claims

1. A method for pharmacokinetic modeling of an image dataset comprising a set of volumes of interest having a plurality of volumes, each volume comprising at least one voxel having at least one related data value, said method comprising

assigning an initial set of parameter values to initial parameters describing a first type of voxel within said image dataset,

calculating a mean voxel data value for each volume in an initial set of volumes of interest comprised in said set of volumes of interest,

reconstructing parameters for each volume in said initial set of volumes of interest, based on said mean voxel data value and said initial set of parameter values, resulting in a subsequent set of parameters, and

assigning said subsequent set of parameters as initial parameters to a subsequent set of volumes of interest comprised in said image dataset.

2. The method according to claim 1, comprising creating a parametric map, having a spatial resolution, for said image dataset by iteratively repeating said calculating, said reconstructing, and said assigning, using each subsequent set of parameters as said initial parameters and each subsequent volume of interest as said initial set of volume of interest, resulting in a predetermined spatial resolution of said parametric map.

3. The method according to claim 2, comprising stopping said repeating by user interaction, independently of said predetermined spatial resolution of said parametric map.

4. The method according to claim 1, further comprising iteratively repeating said calculating, said reconstructing, and said assigning, using each subsequent set of parameters as said initial parameters and each subsequent volume of interest as said initial set of volume of interest until the total number of iterations is equal to a predetermined number of iterations.

5. The method according to claim 1, wherein said image dataset is a 2D, 3D, or higher-dimensional medical image dataset.

6. The method according to claim 1, wherein said subsequent set of volumes of interest is a sub-volume of said initial set of volumes of interest according to a partitioning scheme.

7. The method according to claim 6, wherein said partitioning scheme is predetermined.

8. The method according to claim 6, comprising calculating said partitioning scheme based on two subsequent sets of initial parameters.

9. The method according to claim 1, wherein said subsequent volume of interest is identical to said initial set of volumes of interest.

10. The method according to claim 1, wherein at least one of said initial set of volumes of interest and said subsequent set of volumes of interest is a voxel.

11. The method according to claim 1, said reconstructing of parameters comprising, in successive iteration steps, increasing a reconstruction complexity of said reconstructing of parameters.

12. The method according to claim 1, wherein said reconstructing of parameters is based on a one-compartment model, a two-compartment model or higher order compartment model.

13. The method according to claim 1, wherein said first type of voxel describes healthy tissue.

19. Use of the method, apparatus or computer-readable medium according to claim 1, for diagnosing a disorder or disease in a human.

14. An apparatus (60) for pharmacokinetic modeling of an image dataset comprising a set of volumes of interest having a plurality of volumes, each volume comprising at least one voxel having at least one related data value, said apparatus comprising

a first assigning unit (61) for assigning an initial set of parameter values to initial parameters describing a first type of voxel within said image dataset,

a calculation unit (62) for calculating a mean voxel data value for each volume in an initial set of volumes of interest comprised in said set of volumes of interest,

a reconstruction unit (63) for reconstructing parameters for each volume in said initial set of volumes of interest, based on said mean voxel data value and said initial set of parameter values, resulting in a subsequent set of parameters, and

a second assigning unit (64) for assigning said subsequent set of parameters as initial parameters to a subsequent set of volumes of interest comprised in said image dataset.

15. The apparatus (60) according to claim 14, further comprising a repeating unit (65) for iteratively repeating said calculating, said reconstructing, and said assigning, using each subsequent set of parameters as said initial parameters and each subsequent volume of interest as said initial set of volume of interest until a parametric map having a predetermined resolution is achieved.

16. The apparatus (60) according to claim 15, further comprising a render unit (66) for rendering a 2D or 3D visualization of said image dataset based on said parametric map.

17. The apparatus according to claim 14, being comprised in a medical workstation or a medical imaging system.

18. A computer-readable medium (70) having embodied thereon a computer program for processing by a computer, for pharmacokinetic modeling of an image dataset comprising a set of volumes of interest having a plurality of volumes, each volume comprising at least one voxel having at least one related data value, said computer program comprising

a first assigning code segment (71) for assigning an initial set of parameter values to initial parameters describing a first type of voxel within said image dataset,

a calculation code segment (72) for calculating a mean voxel data value for each volume in an initial set of volumes of interest comprised in said set of volumes of interest,

a reconstruction code segment (73) for reconstructing parameters for each volume in said initial set of volumes of interest, based on said mean voxel data value and said initial set of parameter values, resulting in a subsequent set of parameters, and

a second assigning code segment (74) for assigning said subsequent set of parameters as initial parameters to a subsequent set of volumes of interest comprised in said image dataset.