Registration and visualization of image structures based on confiners

• US 20100111420A1
• Filed: 09/04/2009
• Published: 05/06/2010
• Est. Priority Date: 09/04/2008
• Status: Abandoned Application

• Current Assignee: Julian Mattes
• Original Assignee: Julian Mattes
• Inventors: Gall, Johannes, Mattes, Julian
• Application Number:
  US12/554,392
• Publication Number:
  US 20100111420A1
• Time in Patent Office: Days
• US Class Current: 382/190
• CPC Class Codes: G06T 7/33 using feature-based methods

Abstract

A method for registration of image structures is provided which comprises the steps of providing a source image and a target image each comprising a plurality of pixels, wherein each pixels has a gray value, defining at least one gray value level, determining one or more first regions in the source image for each gray value level as confiners, wherein the first region comprises pixels having gray intensities equal to or higher than the gray value level, selecting one of the one or more determined first regions, determining second regions in the target image which are equal to the selected first regions, calculating the mass of each determined second region by forming the sum of the gray intensities of all pixels of the determined second region, and determining the maximum of the calculated masses and selecting the second region having the maximum mass as corresponding to the first region in the target image.

Claims

1. Method for registration of image structures, comprising:

providing a source image and a target image each comprising a plurality of pixels, wherein each pixels has a gray value;

defining at least one gray value level;

determining one or more first regions in the source image for each gray value level as confiners, wherein the first region comprises pixels having gray values equal to or higher than the gray value level;

selecting one of the one or more determined first regions;

determining at least one second region having a maximum mass in the target image wherein said mass is calculated from the sum of the gray values of all pixels of the second region and having an area corresponding to the selected respective first region, wherein said maximum mass has reached a maximum for at least one second region or a sum of one or more second regions.

2. The method according to claim 1, wherein the source and the target images are two-dimensional or three-dimensional images, respectively;

wherein when the images are two-dimensional images a contour is determined for each first region and wherein when the images are three-dimensional images a surface is determined for each first region.

3. The method according to claim 1, further comprising generating a confinement tree wherein each of the one or more confiners of one gray value level defining nodes on the same level of the tree, the root is defined by the confiner at the first of the gray value levels.

4. The method according to claim 1, further comprising loping the confinement tree by removing nodes from the confinement tree.

5. The method according to claim 1, wherein determining second regions further comprises a mapping of the selected first region in the source image into the target image as second region by applying an initial geometric transformation, and selecting a region of the target image as the selected second region by further transforming the second region in the target image.

6. The method according to claim 1, wherein determining the maximum of the calculated masses comprises maximizing a cost function comprising a similarity measure, wherein the similarity to be maximized is defined as the mass of the region in the target image.

7. The method according to claim 1, wherein said regions of different confiners in the source image are registered independently from each other but their respective initial position depend on the position of the regions of other confiners.

8. The method according to claim 3, wherein said at least one confiner is selected successively and hierarchically from the confinement tree of the source image, from its root down to its leaves, and wherein registration of each selected confiner by determining said second regions is initialized by the result obtained for the preceding confiner in the current confinement tree branch.

9. The method according to claim 1, wherein a common rigid or non-rigid transformation model and a common cost function is used to register several confiners, and, in particular, wherein this non-rigid transformation model is volume preserving in the case of 3D images or area preserving in the case of 2D images.

10. The method according to claim 1, wherein ranges of consecutive gray levels are considered and wherein for each such range a common transformation model and cost functional is used for all selected confiners in the considered range and wherein the registration process for a given range is initialized by the transformation obtained for the previous range with lower gray values.

11. The method according to claim 1, further comprising visualizing the selected first region and/or the selected second region on the target image.

12. The method according to claim 1, wherein the step of visualizing comprises visualizing the confiner, or an approximation of it, with smallest area, in case of a 2D image, or volume, in case of a 3D image, among all confiners of the loped confinement tree containing a given interactively or automatically determined point.

13. An apparatus for registration of image structures which is adapted to carry out a method according to claim 1.

14. A computer program containing computer program code which when executed on a data processing system carries out a method according to claim 1.

15. An electronic storage medium for storing executable program code which when executed on a data processing system carries out a method according to claim 1.