Semi-automated image segmentation system and method

• US 10,275,881 B2
• Filed: 12/29/2016
• Issued: 04/30/2019
• Est. Priority Date: 12/31/2015
• Status: Active Grant

• Current Assignee: ACIST Medical Systems Incorporated (Bracco SPA), Val-chum, Limited Partnership
• Original Assignee: ACIST Medical Systems Incorporated (Bracco SPA), Val-chum, Limited Partnership
• Inventors: Cardinal, Marie-Helene Roy, Destrempes, Francois, Jamello, Joseph A., Cloutier, Guy, Waters, Kendall R., Moore, Thomas C.
• Primary Examiner(s): Tsai, Tsung Yin
• Application Number:
  US15/393,430
• Publication Number:
  US 20170193658A1
• Time in Patent Office: 852 Days
• CPC Class Codes: A61B 5/0066 Optical coherence imaging
• CPC Class Codes: A61B 5/0084 for introduction into the body, e.g. by catheters A61B5/1459 takes precedence
• CPC Class Codes: A61B 8/12 in body cavities or body tracts, e.g. by using catheters catheters per se A61M25/00
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2207/10068 Endoscopic image
• CPC Class Codes: G06T 2207/10101 Optical tomography; Optical coherence tomography [OCT]
• CPC Class Codes: G06T 2207/10132 Ultrasound image
• CPC Class Codes: G06T 2207/20092 Interactive image processing based on input by user
• CPC Class Codes: G06T 2207/20101 Interactive definition of point of interest, landmark or seed
• CPC Class Codes: G06T 2207/30101 Blood vessel; Artery; Vein; Vascular
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/12 Edge-based segmentation
• CPC Class Codes: G06T 7/143 involving probabilistic approaches, e.g. Markov random field [MRF] modelling
• CPC Class Codes: G06T 7/149 involving deformable models, e.g. active contour models

Abstract

Image segmentation can include a pre-initialization image analysis of image data using an image analysis algorithm to generate a modified image, and the modified image can be presented on a display. An initialization can be performed on the modified image that includes user input on the modified image. The modified image can be segmented using a segmentation algorithm that evaluates the user input. Upon evaluating the user input, the segmentation algorithm can cause a segmented image to be produced which can be presented on the display.

Claims

1. A method of segmenting an image, the method comprising the steps of:

performing a pre-initialization image analysis of image data using an image analysis algorithm to generate a modified image and presenting the modified image on a display, wherein the image data represents a plurality of image elements;

performing an initialization of the modified image generated by the pre-initialization image analysis, wherein performing the initialization includes receiving a user input on the modified image on the display; and

segmenting the modified image using a segmentation algorithm that evaluates the received user input of the performed initialization and displaying a segmented image on the display,

wherein the modified image includes a proposed control contour and the proposed control contour on the modified image on the display comprises a first visual indicator along a first portion of the proposed control contour and a second visual indicator along a second portion of the proposed control contour, wherein the first and second visual indicators are different and one of the first and second visual indicators designates that the respective portion of the proposed control contour is below a threshold level of information determined by the pre-initialization image analysis, and

wherein the second visual indicator along the second portion of the proposed control contour designates that the second portion of the proposed control contour is below a threshold level of information, and wherein the second visual indicator comprises one of a color different from a color of the first visual indicator and a line pattern different from a line pattern of the first visual indicator.

2. The method of claim 1, further comprising:

generating the image data used in the pre-initialization image analysis representing the plurality of image elements with an intravascular ultrasound imaging system.

3. The method of claim 2, wherein generating the image data with the intravascular ultrasound imaging system comprises:

collecting cross-sectional image data using a catheter assembly that includes an intravascular imaging device having an imaging module for emitting and receiving energy.

4. The method of claim 3, wherein the intravascular imaging device comprises an ultrasound transducer configured to emit and receive ultrasound energy.

5. The method of claim 1, wherein the image analysis algorithm includes calculating a probability density function of the image data.

6. The method of claim 1, wherein the image analysis algorithm includes calculating a gradient function of the image data.

7. The method of claim 1, wherein the modified image is clearer relative to an image generated using the image data before the pre-initialization image analysis of the image data is performed.

8. The method of claim 1, wherein receiving the user input on the modified image on the display comprises receiving a confirmation of a proposed control contour, or a portion thereof, presented on the modified image on the display.

9. The method of claim 1, wherein receiving the user input on the modified image on the display comprises receiving a modification of a proposed control contour, or a portion thereof, presented on the modified image on the display.

10. The method of claim 1, wherein receiving the user input on the modified image on the display comprises receiving a control contour placed on the modified image on the display.

11. The method of claim 10, wherein the control contour is placed at or near a location of a lumen-intima interface on the modified image on the display.

12. The method of claim 10, wherein the control contour is placed at or near a location of a media-adventitia interface on the modified image on the display.

13. The method of claim 10, wherein the control contour is placed on a longitudinal image on the display and a first control point is generated on a first cross-sectional image on the display, wherein the first control point corresponds to a location of the control contour on the first cross-sectional image.

14. The method of claim 13, wherein the first control point is generated on the longitudinal image on the display and a second control point is generated on the longitudinal image on the display, wherein the second control point corresponds to a location of the control contour on a second cross-sectional image, and wherein the first cross-sectional image and the second cross-sectional image are spaced apart along the longitudinal image by a predetermined interval of cross-sectional images.

15. The method of claim 1, wherein the threshold level of information determined by the pre-initialization image analysis comprises a signal-to-noise ratio of the image data, and wherein the second visual indicator designates that the respective portion of the proposed control contour is below the threshold level signal-to-noise ratio of the image data.

16. The method of claim 1, wherein the image analysis algorithm increase contrast between neighboring image elements in the image data, wherein the modified image is presented on the display with the increased contrast between neighboring image elements, wherein the initialization is performed after the pre-initialization image analysis, and wherein the segmenting is performed after the initialization.

17. A method of segmenting an image, the method comprising the steps of:

performing a pre-initialization image analysis of image data using an image analysis algorithm to generate a modified image and presenting the modified image on a display, wherein the image data represents a plurality of image elements;

performing an initialization of the modified image generated by the pre-initialization image analysis, wherein performing the initialization includes receiving a user input on the modified image on the display; and

segmenting the modified image using a segmentation algorithm that evaluates the received user input of the performed initialization and displaying a segmented image on the display,

wherein the modified image includes a proposed control contour and the proposed control contour on the modified image on the display comprises a first visual indicator along a first portion of the proposed control contour and a second visual indicator along a second portion of the proposed control contour, wherein the first and second visual indicators are different and one of the first and second visual indicators designates that the respective portion of the proposed control contour is below a threshold level of information determined by the pre-initialization image analysis, and

wherein the threshold level of information determined by the pre-initialization image analysis comprises a signal-to-noise ratio of the image data, and wherein one of the first and second visual indicators designates that the respective portion of the proposed control contour is below the threshold level signal-to-noise ratio of the image data.

18. The method of claim 17, wherein the one of the first and second visual indicators that designates that the respective portion of the proposed control contour is below the threshold level signal-to-noise ratio of the image data comprises one of a different color and a line pattern.

19. The method of claim 17, wherein the image analysis algorithm increase contrast between neighboring image elements in the image data, wherein the modified image is presented on the display with the increased contrast between neighboring image elements, wherein the initialization is performed after the pre-initialization image analysis, and wherein the segmenting is performed after the initialization.

20. The method of claim 17, wherein the image analysis algorithm includes calculating a probability density function of the image data.

21. The method of claim 17, wherein the image analysis algorithm includes calculating a gradient function of the image data.

22. The method of claim 17, wherein the modified image is clearer relative to an image generated using the image data before the pre-initialization image analysis of the image data is performed.

23. The method of claim 17, wherein the proposed control contour is placed on a longitudinal image on the display and a first control point is generated on a first cross-sectional image on the display, wherein the first control point corresponds to a location of the proposed control contour on the first cross-sectional image.

24. The method of claim 23, wherein the first control point is generated on the longitudinal image on the display and a second control point is generated on the longitudinal image on the display, wherein the second control point corresponds to a location of the proposed control contour on a second cross-sectional image, and wherein the first cross-sectional image and the second cross-sectional image are spaced apart along the longitudinal image by a predetermined interval of cross-sectional images.

25. A non-transitory computer-readable storage article having computer-executable instructions stored thereon to cause at least one programmable processor to:

perform a pre-initialization image analysis of image data using an image analysis algorithm to generate a modified image and present the modified image on a display, wherein the image data represents a plurality of image elements, wherein the image analysis algorithm increases contrast between neighboring image elements in the image data, and wherein the modified image is presented on the display with the increased contrast between neighboring image elements;

after the pre-initialization image analysis, perform an initialization of the modified image generated by the pre-initialization image analysis, wherein the initialization includes receiving a user input on the modified image on the display; and

after the initialization of the modified image, segment the modified image using a segmentation algorithm that evaluates the received user input of the initialization and display a segmented image on the display.

26. The article of claim 25, wherein the image analysis algorithm includes calculating a probability density function of the image data.

27. The article of claim 25, wherein the received user input on the modified image on the display comprises a control contour placed on the modified image on the display.

28. The article of claim 25, wherein the modified image includes a proposed control contour and the proposed control contour on the modified image on the display comprises a first visual indicator along a first portion of the proposed control contour and a second visual indicator along a second portion of the proposed control contour, wherein the first and second visual indicators are different and one of the first and second visual indicators designates that the respective portion of the proposed control contour is below a threshold level of information determined by the pre-initialization image analysis.

29. The article of claim 28, wherein the second visual indicator along the second portion of the proposed control contour designates that the second portion of the proposed control contour is below a threshold level of information, and wherein the second visual indicator comprises one of a color different from a color of the first visual indicator and a line pattern different from a line pattern of the first visual indicator.

30. The article of claim 28, wherein the threshold level of information determined by the pre-initialization image analysis comprises a signal-to-noise ratio of the image data, and wherein one of the first and second visual indicators designates that the respective portion of the proposed control contour is below the threshold level signal-to-noise ratio of the image data.

31. The article of claim 28, wherein the proposed control contour is placed on a longitudinal image on the display and a first control point is generated on a first cross-sectional image on the display, wherein the first control point corresponds to a location of the proposed control contour on the first cross-sectional image.

32. The article of claim 31, wherein the first control point is generated on the longitudinal image on the display and a second control point is generated on the longitudinal image on the display, wherein the second control point corresponds to a location of the proposed control contour on a second cross-sectional image, and wherein the first cross-sectional image and the second cross-sectional image are spaced apart along the longitudinal image by a predetermined interval of cross-sectional images.