Granted Patent B2

US 12,254,586 · App. 17/939,015 · Granted Mar 18, 2025

Inventors: Herschel A. Solis (Santa Clara, CA); Calvin J. Wong (Fremont, CA)

Assignee: Hologic, Inc.

G06T3/40A61B5/7425G06T3/20G06T7/11G06V10/25G06T2200/24G06T2207/10088G06T2207/10132G06T2207/20104G06T2207/30068

Abstract

Claims (48)

1. A system comprising:

a processor; and

memory coupled to the processor, the memory comprising computer executable instructions that, when executed, perform a method comprising:

receiving a selection of a region of interest (ROI) in a first image of a plurality of images;

identifying, using an auto-focus tool, a location of the ROI within the first image based on at least one of spacing of image pixel data, thickness of a slice image, and location of the slice image;

converting, via a mapping function of the auto-focus tool, first ROI identification information of the first image to second ROI identification of at least a second image of the plurality of images, wherein the first ROI identification information and the second ROI identification information are a different type, the first ROI identification information includes image view information and the second ROI identification information includes image header information;

identifying, using the auto-focus tool, an area corresponding to the location of the ROI in at least the second image of the plurality of images, wherein the first image and the second image are different imaging modality types and an automated determination mechanism is used to identify the area corresponding to the location of the ROI; and

causing the auto-focus tool to automatically:

focus a first field of view on the ROI in the first image; and

focus a second field of view on the area corresponding to the location of the ROI in the second image.

2. The system of claim 1 , wherein the system is an electronic image review system for reviewing medical images within a healthcare environment.

3. The system of claim 1 , wherein focusing the first field of view on the ROI in the first image comprises centering the ROI within the first field of view and scaling the ROI to increase or decrease a size of the ROI within the first field of view.

4. The system of claim 1 , wherein the imaging modality types include at least two of: mammography, MRI, or ultrasound.

5. The system of claim 1 , wherein the first image is generated during a current patient visit for a patient and the second image was generated during a previous patient visit for the patient.

6. The system of claim 1 , wherein the plurality of images is arranged for viewing based on an image viewing layout specified by a user, the image viewing layout enabling the plurality of images to be concurrently presented to a user.

7. The system of claim 1 , wherein receiving the selection of the ROI comprises:

receiving a selection of a point in the first image; and

defining an area surrounding the point as the ROI.

8. The system of claim 7 , wherein, in response to receiving the selection of the point in the first image, a bounding box comprising at least a portion of the ROI is applied to the image.

9. The system of claim 8 , wherein the bounding box is automatically applied such that at least a first object in the first image is delineated from at least a second object in the first image.

10. The system of claim 1 , wherein receiving the selection of the ROI comprises:

receiving a selection of a plurality of points in the first image;

determining a centroid of the plurality of points; and

defining an area surrounding the centroid as the ROI.

11. The system of claim 1 , wherein the automated determination mechanism is at least one of: a rule set, a mapping algorithm, or an image or object classifier.

12. The system of claim 1 , wherein a process for identifying the location of the ROI within the first image is based on the imaging modality type of the first image.

13. The system of claim 12 , wherein the process for identifying the location of the ROI within the first image includes the use of at least one of: image view information, spatial coordinate information, image header information, or image orientation data.

14. The system of claim 1 , wherein, when the first image and a third image of the plurality of images are a same imaging modality type, the mapping function is used to map the first ROI identification information of the first image to third ROI identification information of the third image, wherein the first ROI identification information and the third ROI identification information are a same type.

15. The system of claim 1 , wherein focusing the first field of view on the ROI in the first image comprises orienting the first image such that the ROI is at least one of horizontally or vertically centered in a viewport comprising the first image.

16. The system of claim 1 , wherein focusing the second field of view on the area corresponding to the location of the ROI in the second image comprises applying a scaling factor to the area corresponding to the location of the ROI.

17. A method comprising:

receiving, at an image review device, a selection of a region of interest (ROI) in a first image of a plurality of images;

identifying, using an auto-focus tool, a location of the ROI within the first image based on at least one of spacing of image pixel data, thickness of a slice image, and location of the slice image;

converting, via a mapping function of the auto-focus tool, first ROI identification information of the first image to second ROI identification of at least a second image of the plurality of images, wherein the first ROI identification information and the second ROI identification information are a different type, the first ROI identification information includes image view information and the second ROI identification information includes image header information;

identifying, using the auto-focus tool, an area corresponding to the location of the ROI in at least the second image of the plurality of images, wherein the first image and the second image are different imaging modality types and an automated determination mechanism is used to identify the area corresponding to the location of the ROI; and

causing the auto-focus tool to automatically:

focus a first field of view on the ROI in the first image; and

focus a second field of view on the area corresponding to the location of the ROI in the second image.

18. The method of claim 1 , wherein the plurality of images comprises at least a mammography image, an MRI image, and an ultrasound image.

19. A computing device comprising:

a processor; and

an image auto-focus tool configured to:

receive a selection of a region of interest (ROI) in a first image of a plurality of images;

identify a location of the ROI within the first image based on at least one of spacing of image pixel data, thickness of a slice image, and location of the slice image;

convert, via a mapping function of the auto-focus tool, first ROI identification information of the first image to second ROI identification of at least a second image of the plurality of images, wherein the first ROI identification information and the second ROI identification information are a different type, the first ROI identification information includes image view information and the second ROI identification information includes image header information;

identify an area corresponding to the location of the ROI in at least the second image of the plurality of images, wherein the first image and the second image are different imaging modality types and an automated determination mechanism is used to identify the area corresponding to the location of the ROI;

focus a first field of view on the ROI in the first image; and

focus a second field of view on the area corresponding to the location of the ROI in the second image, wherein focusing the second field of view comprises at least one of scaling the second image or panning the second image.

Assignments (4)

Continuity (2)

References Cited (400)