IMAGE PROCESSING APPARATUS AND IMAGE PROCESSING METHOD FOR A TOMOGRAM OF AN EYE REGION

• US 20100202677A1
• Filed: 04/13/2010
• Published: 08/12/2010
• Est. Priority Date: 10/17/2008
• Status: Active Grant

• Current Assignee: Canon Kabushiki Kaisha (Canon Inc.)
• Original Assignee: Canon Kabushiki Kaisha (Canon Inc.)
• Inventors: Iwase, Yoshihiko, Imamura, Hiroshi, Katayama, Akihiro, Satoh, Kiyohide
• Granted Patent: US 8,442,286 B2
• Time in Patent Office: Days
• US Class Current: 382/131
• CPC Class Codes: A61B 3/0025 characterised by electronic signal processing, e.g. eye models
• CPC Class Codes: A61B 3/102 for optical coherence tomography [OCT]
• CPC Class Codes: A61B 3/12 for looking at the eye fundus, e.g. ophthalmoscopes A61B3/13 takes precedence
• CPC Class Codes: A61B 5/0066 Optical coherence imaging
• CPC Class Codes: G06T 2207/10072 Tomographic images
• CPC Class Codes: G06T 2207/30041 Eye; Retina; Ophthalmic
• CPC Class Codes: G06T 7/0012 Biomedical image inspection

Abstract

There is provided a technique for adaptively acquiring, from a tomogram of an eye region, diagnosis information data of the eye region which is used for the diagnosis of a plurality of kinds of diseases, without increasing load on a user. A layer acquisition unit (331) acquires a predetermined layer area from the tomogram of the eye region. A changing unit (332) changes an algorithm for the acquisition of diagnosis information data as information used for the diagnosis of the eye region from the tomogram based on the information data extracted from the layer area. A quantifying unit (336) acquires diagnosis information data from the tomogram based on the changed algorithm.

Claims

1. An image processing apparatus which processes a tomogram of an eye region, comprising:

layer acquisition means for acquiring a predetermined layer area from the tomogram;

changing means for changing an algorithm for acquiring, based on information data extracted from the layer area, diagnosis information data as information to be used for diagnosis of the eye region from the tomogram; and

means for acquiring the diagnosis information data from the tomogram based on the algorithm changed by said changing means.

2. The image processing apparatus according to claim 1, further comprising image acquisition means for acquiring the tomogram.

3. The image processing apparatus according to claim 1, wherein said changing means comprises state determination means for determining a state of the layer based on the layer area acquired by said layer acquisition means, and changes the algorithm in accordance with a determination result obtained by said state determination means.

4. The image processing apparatus according to claim 3, wherein said state determination means determines whether a state of the predetermined layer is normal.

5. The image processing apparatus according to claim 3, further comprising second layer acquisition means for acquiring a second layer area as information for acquiring the diagnosis information data from the tomogram,

wherein said changing means determines, in accordance with a determination result obtained by said state determination means, whether said second layer acquisition means is to acquire the second layer area.

6. The image processing apparatus according to claim 3, further comprising normal structure estimation means for estimating a normal structure of the layer on the tomogram as information for acquiring the diagnosis information data,

wherein said changing means determines to execute estimation of a normal structure using said normal structure estimation means, when said state determination means determines that the state of the layer is not normal.

7. The image processing apparatus according to claim 3, wherein said changing means changes a target area for image processing for acquisition of the diagnosis information data, a direction of processing, a processing sequence, and processing intervals based on a position, area or volume, and shape of an abnormal region of the layer, when said state determination means determines that the state of the layer is not normal.

8. The image processing apparatus according to claim 1, further comprising quantifying means for quantifying a state of the layer by using one of a shape and layer thickness of the layer area obtained by said layer acquisition means.

9. The image processing apparatus according to claim 6, further comprising quantifying means for quantifying a state of the layer by using one of a thickness distribution, area, volume, density feature indicated by a difference between the layer area obtained by said layer acquisition means and a normal structure of the layer estimated by said normal structure estimation means.

10. The image processing apparatus according to claim 1, further comprising:

instruction acquisition means for externally acquiring an instruction to store or not to store an acquisition result obtained by said layer acquisition means, and

output means for outputting the acquisition result obtained by said layer acquisition means when said instruction acquisition means acquires an instruction to store.

11. The image processing apparatus according to claim 3, wherein

the predetermined layer is at least one of layers existing in a range from an internal limiting membrane to an inner plexiform layer, and

said state determination means determines whether a state of the layer is normal, by using at least one piece of information of a layer thickness detected by said layer acquisition means and an index indicating an indentation shape or statistics thereof.

12. The image processing apparatus according to claim 3, wherein

the predetermined layer is at least one of layers existing in a range from an external limiting membrane to a pigmented retinal layer, and

said state determination means determines whether the state of the layer is normal, by using at least one piece of information of information indicating a presence/absence of the layer and a layer thickness which are detected by said layer acquisition means and statistics concerning an extreme value of a point sequence constituting the detected layer, the number of inflection points, a curvature, and an angle.

13. The image processing apparatus according to claim 3, wherein the predetermined layer is an overall retinal layer, and said state determination means determines whether the state of the layer is normal, by using information indicating a presence/absence of the layer and a layer thickness which are detected by said layer acquisition means.

14. The image processing apparatus according to claim 1, wherein the predetermined layer is at least one of layers existing in a range from an internal limiting membrane to an inner plexiform layer.

15. The image processing apparatus according to claim 1, wherein the predetermined layer is at least one of layers existing in a range from an external limiting membrane to a pigmented retinal layer.

16. The image processing apparatus according to claim 1, wherein the predetermined layer is an overall retinal layer.

18. A computer program for causing a computer to function as each means included in the image processing apparatus defined in claim 1.

19. A computer-readable storage medium which stores the computer program defined in claim 18.

17. An image processing method performed by an image processing apparatus which processes a tomogram of an eye region, comprising:

a layer acquisition step of acquiring a predetermined layer area from the tomogram;

a changing step of changing an algorithm for acquiring, based on information data extracted from the layer area, diagnosis information data as information to be used for diagnosis of the eye region from the tomogram; and

a step of acquiring the diagnosis information data from the tomogram based on the algorithm changed in the changing step.