Interaction method for regions of-interest in time series images

1. A method for identifying a region of interest within a time sequence of images, comprising:

acquiring a time sequence of images comprising a plurality of image frames;

performing image segmentation to segment a first region of interest (ROI) and a second ROI from within each of the plurality of image frames of the time sequence of images;

receiving one or more manual edits to the first ROI within a first keyframe for the first ROI of the plurality of image frames;

receiving one or more manual edits to the ROI within a second keyframe for the first ROI of the plurality of image frames;

receiving one or more manual edits to the second ROI within a first keyframe for the second ROI of the plurality of image frames;

receiving one or more manual edits to the second ROI within a second keyframe for the second ROI of the plurality of image frames;

propagating the manual edits corresponding to the first ROI to other image frames of the plurality of images, the other image frames being those image frames of the plurality of image frames that are neither the first keyframe for the first ROI nor the second keyframe for the first ROI; and

propagating the manual edits corresponding to the second ROI to other image frames of the plurality of images, the other image frames being those image frames of the plurality of image frames that are neither the first keyframe for the second ROI nor the second keyframe for the first ROI,

wherein an extent to which each of the manual edits for the first and second ROI are propagated to other image frames is dependent upon a distance in time between each of the other image frames and the first and second keyframes that have been manually edited for the first ROI, respectively, and

wherein the first keyframe for the first ROI, the second keyframe for the first ROI, the first keyframe for the second ROI, and the second keyframe for the second ROI are all different frames of the plurality of image frames.

2. The method of claim 1 , wherein the extent to which each of the manual edits are propagated to other image frames is dependent upon a transformation function or deformation field used to propagate the manual edits and a weighing factor that is influenced by the distance in time between the other image frames and the first or second keyframes that have been manually edited.

3. The method of claim 1 , wherein propagating manual edits to the other image frames includes, for each of the other image frames, determining a first transformation based on an effect of manual edits to a frame of the plurality of image frames nearest to the left of a manually edited keyframe of the first and second keyframes, determining a second transformation based on an effect of manual edits to a frame of the plurality of image frames nearest to the right of the manually edited keyframe of the first and second keyframes, and calculating a new contour for each of the other image frames by combining the first transformation and the second transformation in accordance with a weighing that is proportional to the distance between the other image frame and the nearest left manually edited keyframe of the first and second keyframes and the nearest right manually edited keyframe of the first and second keyframes.

4. The method of claim 1 , wherein the time sequence of images is considered circular such that the first image of the time sequence of images is understood to follow the last image of the time sequence of images and manual edits are propagated past the last image to the first image.

5. The method of claim 1 , wherein the region of interest is a contour, one or more landmarks, or a group of pixels.

6. The method of claim 1 , wherein multiple regions of interest are identified within the time sequence of images.

7. The method of claim 1 , wherein the time sequence of images includes a sequence of x-rays, magnetic resonance (MR) images, or computed tomography (CT) images.

8. The method of claim 1 , wherein the ROI delineates a particular anatomical structure, region of disease or injury, or foreign body that is observable within the time sequence of images.

9. The method of claim 1 , wherein each image frame of the time sequence of images is a two-dimensional image.

10. The method of claim 1 , wherein each image frame of the time sequence of images is a three-dimensional image.

11. The method of claim 1 , wherein image segmentation is automatically performed using a computer algorithm.

12. The method of claim 1 , wherein the manual edits are provided by a human user and include manual adjustments to the ROI to more accurately represent a particular structure.

13. The method of claim 1 , wherein propagation of the manual edits to the other image frames includes modifying the ROI of one or more of the image frames that have not been manually edited in a manner similar to the manner of the manual edits.

14. The method of claim 1 , wherein the extent to which each of the manual edits are propagated to other image frames is inversely proportional to the distance in time between the other image frames and the keyframe that have been manually edited.

15. A method for identifying a region of interest within a time sequence of images, comprising:

acquiring a time sequence of images comprising a plurality of image frames;

performing image segmentation to segment a first region of interest (ROI) and a second ROI from within each of the plurality of image frames of the time sequence of images;

receiving manual edits to the first ROI within a first edited image frame for the first ROI of the plurality of image frames;

receiving manual edits to the first ROI within a second edited image frame for the first ROI of the plurality of image frames;

receiving manual edits to the second ROI within a first edited image frame for the first ROI of the plurality of image frames;

receiving manual edits to the second ROI within a second edited image frame for the first ROI of the plurality of image frames;

propagating the manual edits to the first ROI within the first edited image frame for the first ROI to image frames of the plurality of images preceding the first edited image frame for the first ROI and to image frames between the first edited image frame for the first ROI and the second edited image frame for the first ROI, to an extent that is dependent upon a first transformation function used to propagate the manual edits to the first ROI within the first edited image and a first weighing factor that is dependent upon a distance between the image frames and the first edited image frame for the first ROI;

propagating the manual edits to the first ROI within the second edited image frame for the first ROI to image frames of the plurality of images subsequent to the second edited image frame for the first ROI and to image frames between the first edited image frame for the first ROI and the second edited image frame for the first ROI, to an extent that is dependent upon a second transformation function used to propagate the manual edits to the first ROI within the second edited image for the first ROI and a second weighing factor that is dependent upon a distance between the image frames and the second edited image frame for the first ROI;

propagating the manual edits to the second ROI within the first edited image frame for the second ROI to image frames of the plurality of images preceding the first edited image frame for the second ROI and to image frames between the first edited image frame for the second ROI and the second edited image frame for the second ROI, to an extent that is dependent upon a third transformation function used to propagate the manual edits to the second ROI within the first edited image and a first weighing factor that is dependent upon a distance between the image frames and the first edited image frame for the second ROI; and

propagating the manual edits to the second ROI within the second edited image frame for the second ROI to image frames of the plurality of images subsequent to the second edited image frame for the second ROI and to image frames between the first edited image frame for the second ROI and the second edited image frame for the second ROI, to an extent that is dependent upon a fourth transformation function used to propagate the manual edits to the first ROI within the second edited image for the second ROI and a second weighing factor that is dependent upon a distance between the image frames and the second edited image frame for the second ROI,

wherein the image frames between the first and second edited image frames for the first ROI transition from being fully influenced by the manual edits of the first edited image frame for the first ROI and not at all influenced by the manual edits of the second edited image frame to being fully influenced by the manual edits of the second edited image frame for the first ROI and not at all influenced by the manual edits of the first edited image frame for the first ROI, and

wherein the image frames between the first and second edited image frames for the second ROI transition from being fully influenced by the manual edits of the first edited image frame for the second ROI and not at all influenced by the manual edits of the second edited image frame to being fully influenced by the manual edits of the second edited image frame for the second ROI and not at all influenced by the manual edits of the first edited image frame for the second ROI.

16. The method of claim 15 , wherein the first edited image is a first keyframe and the second edited image is a second keyframe.

17. The method of claim 15 , wherein region of interest is a contour, one or more landmarks, or a group of pixels.

18. The method of claim 15 , wherein multiple regions of interest are identified within the time sequence of images.

19. The method of claim 15 , wherein the time sequence of images includes a sequence of x-rays, magnetic resonance (MR) images, or computed tomography (CT) images.

20. The method of claim 15 , wherein the ROI delineates a particular anatomical structure, region of disease or injury, or foreign body that is observable within the time sequence of images.

21. The method of claim 15 , wherein each image frame of the time sequence of images is a two-dimensional image.

22. The method of claim 15 , wherein each image frame of the time sequence of images is a three-dimensional image.

23. The method of claim 15 , wherein image segmentation is automatically performed using a computer algorithm.

24. The method of claim 15 , wherein the manual edits are provided by a human user and include manual adjustments to the ROI to more accurately represent a particular structure.

25. The method of claim 15 , wherein propagation of the manual edits to the other image frames includes modifying the ROI of one or more of the image frames that have not been manually edited in a manner similar to the manner of the manual edits.

26. A computer system comprising:

a processor; and

a non-transitory, tangible, program storage medium, readable by the computer system, embodying a program of instructions executable by the processor to perform method steps for identifying a region of interest within a time sequence of images, the method comprising:

acquiring a time sequence of images comprising a plurality of image frames;

performing image segmentation to segment a first region of interest (ROI) and a second ROI from within each of the plurality of image frames of the time sequence of images;

receiving one or more manual edits to the first ROI within a first keyframe for the first ROI of the plurality of image frames;

receiving one or more manual edits to the ROI within a second keyframe for the first ROI of the plurality of image frames;

receiving one or more manual edits to the second ROI within a first keyframe for the second ROI of the plurality of image frames;

receiving one or more manual edits to the second ROI within a second keyframe for the second ROI of the plurality of image frames;

propagating the manual edits corresponding to the first ROI to other image frames of the plurality of images, the other image frames being those image frames of the plurality of image frames that are neither the first keyframe for the first ROI nor the second keyframe for the first ROI; and

propagating the manual edits corresponding to the second ROI to other image frames of the plurality of images, the other image frames being those image frames of the plurality of image frames that are neither the first keyframe for the second ROI nor the second keyframe for the first ROI,

wherein an extent to which each of the manual edits for the first and second ROI are propagated to other image frames is dependent upon a distance in time between each of the other image frames and the first and second keyframes that have been manually edited for the first ROI, respectively, and

wherein the first keyframe for the first ROI, the second keyframe for the first ROI, the first keyframe for the second ROI, and the second keyframe for the second ROI are all different frames of the plurality of image frames.