Method for Presenting Images to Identify Target Objects

• US 20100008541A1
• Filed: 07/08/2008
• Published: 01/14/2010
• Est. Priority Date: 07/08/2008
• Status: Abandoned Application

• Current Assignee: Mitsubishi Electric Research Laboratories, Inc. (Mitsubishi Electric Corporation)
• Original Assignee: Mitsubishi Electric Research Laboratories, Inc. (Mitsubishi Electric Corporation)
• Inventors: Forlines, Clifton L.
• Application Number:
  US12/169,315
• Publication Number:
  US 20100008541A1
• Time in Patent Office: Days
• US Class Current: 382/103
• CPC Class Codes: G06V 10/987 with the intervention of an operator

Abstract

A method presents a set of images to a viewer. The images include objects, which can be either distractor objects or target objects. A prevalence of the target objects is substantially lower than the distractor objects. Each image is segmented into portions so that each portion includes one object. The portions are then combined into a combined image. The combined image is presented to a viewer so that the target objects can be accurately and rapidly identified. The combining of the portions can be random or ordered in either the spatial or temporal domain.

Claims

1. A method for presenting a set of images to a viewer to identify target objects, comprising the steps of:

segmenting a set of images into portions, in which the set of images includes objects, the objects being either distractor objects or target objects, and a prevalence of the target objects is substantially lower than the distractor objects, and in which each portion includes one object;

combining the portions into a combined image; and

presenting the combined image to a viewer to identify the target objects rapidly and accurately.

2. The method of claim 1, in which the combining composites the portions into a single combined image.

3. The method of claim 2, in which the portions are arranged randomly in the single combined image.

4. The method of claim 2, in which the portions are spatially ordered in the single combined image.

5. The method of claim 1, in which the segmenting uses k-means clustering.

6. The method of claim 1, in which the segmenting uses is histogram based.

7. The method of claim 1, in which the segmenting uses edge detection.

8. The method of claim 1, in which the segmenting uses region growing.

9. The method of claim 1, in which the combining increases a prevalence of the target objects in the combined image.

10. The method of claim 1, in which the portions are combined at a same location of a display and presented sequentially over time.

11. The method of claim 10, in which the positions are presented randomly over time.

12. The method of claim 1, in which the segmenting uses a sliding window to sample the portions of each image within the sliding window.

13. The method of claim 12, in which the portions are combined at a same location of a display and presented sequentially over time.

14. The method of claim 1, further comprising:

acquiring the set of images using x-rays.

15. The method of claim 1, in which the set of images are of pathology slides.