Multimodal segmentation in intravascular images

• US 9,770,172 B2
• Filed: 03/07/2014
• Issued: 09/26/2017
• Est. Priority Date: 03/07/2013
• Status: Active Grant

• Current Assignee: Volcano Corporation (Koninklijke Philips N.V.)
• Original Assignee: Volcano Corporation (Koninklijke Philips N.V.)
• Inventors: Sturm, Bernhard
• Primary Examiner(s): Mehta, Bhavesh
• Assistant Examiner(s): Lemieux, Ian
• Application Number:
  US14/200,512
• Publication Number:
  US 20140254900A1
• Time in Patent Office: 1,299 Days
• CPC Class Codes: A61B 2090/364 Correlation of different images or relation of image positions in respect to the body
• CPC Class Codes: A61B 2090/3966 Radiopaque markers visible in an X-ray image
• CPC Class Codes: A61B 5/0035 adapted for acquisition of images from more than one imaging mode, e.g. combining MRI and optical tomography
• CPC Class Codes: A61B 5/0037 Performing a preliminary scan, e.g. a prescan for identifying a region of interest
• CPC Class Codes: A61B 5/061 Determining position of a probe within the body employing means separate from the probe, e.g. sensing internal probe position employing impedance electrodes on the surface of the body A61B1/00158 takes precedence
• CPC Class Codes: A61B 5/489 Blood vessels
• CPC Class Codes: A61B 8/4416 related to combined acquisition of different diagnostic modalities, e.g. combination of ultrasound and X-ray acquisitions
• CPC Class Codes: A61B 8/445 Details of catheter construction
• CPC Class Codes: G06F 18/253 of extracted features
• CPC Class Codes: G06V 2201/03 Recognition of patterns in medical or anatomical images

Abstract

The invention provides methods for detecting features of interest in cardiovascular images by receiving information from a first modality and transforming information from the first modality into a first coordinate space, receiving information from a second modality and transforming information from the second modality into a second coordinate space. The first coordinate space is aligned to the second coordinate space to combine information from the first modality and the second modality into a combined data set. The method can also involve detecting the feature of interest in a vascular image based on the combined data set.

Claims

1. A method for detecting a feature of interest in a vascular image, the

method comprising:

receiving information from a first imaging modality and transforming information from the first imaging modality into a first coordinate space, wherein the first imaging modality comprises an intravascular imaging modality associated with an intravascular device positioned within a vessel of a patient;

receiving information from a second imaging modality and transforming information from the second imaging modality into a second coordinate space, the second imaging modality comprising at least one of ultrasound, photoacoustic imaging, virtual histology intravascular ultrasound (VH-IVUS), optical coherence tomography (OCT), x-ray angiography, fluoroscopy, or magnetic resonance imaging (MRI);

aligning the first coordinate space and the second coordinate space, thereby combining information from the first imaging modality and the second imaging modality into a combined data set; and

detecting a feature of interest in a vascular image based on the combined data set, wherein detection of a feature of interest comprises training an algorithm to detect the feature of interest based on the combined data set and initializing a search for the feature of interest based on the combined data set.

2. The method of claim 1, wherein the first imaging modality is different from the second imaging modality.

3. The method of claim 1, wherein receiving information from the first imaging modality and the second imaging modality comprises receiving information regarding the feature of interest.

4. The method of claim 1, wherein the feature of interest comprises a biological feature of interest.

5. The method of claim 4, wherein the biological feature of interest is a vessel or lumen wall.

6. The method of claim 1, wherein the feature of interest comprises a non-biological feature of interest.

7. The method of claim 6, wherein the non-biological feature of interest is a stent.

8. A system for determining the degree of improvement

after a therapeutic procedure, the system comprising:

a processor; and

a computer readable storage medium comprising instructions that when executed cause the system to;

receive information from a first imaging modality and transform information from the first imaging modality into a first coordinate space, wherein the first imaging modality comprises an intravascular imaging modality associated with an intravascular device positioned within a vessel of a patient;

receive information from a second imaging modality and transform information from the second imaging modality into a second coordinate space, the second imaging modality comprising at least one of ultrasound, photoacoustic imaging, virtual histology intravascular ultrasound (VH-IVUS), optical coherence tomography (OCT), x-ray angiography, fluoroscopy, or magnetic resonance imaging (MRI);

align the first coordinate space and the second coordinate space, thereby combining information from the first imaging modality and the second imaging modality into a combined data set; and

detect a feature of interest in a vascular image based on the combined data set, wherein detection of a feature of interest comprises training an algorithm to detect the feature of interest based on the combined data set and initializing a search for the feature of interest based on the combined data set.

9. The system of claim 8, wherein receiving information comprises receiving information regarding the feature of interest.

10. The system of claim 8, wherein the feature of interest comprises a biological feature of interest.

11. The system of claim 10, wherein the biological feature of interest is a vessel or lumen wall.

12. The system of claim 8, wherein the feature of interest comprises a non-biological feature of interest.

13. The system of claim 12, wherein the non-biological feature of interest is a stent.

14. The system of claim 8, wherein the computer readable storage medium further comprises instructions operable to cause the system to train the algorithm, including instructions to:

obtain a first image with the first imaging modality,

identify the feature of interest within the first image,

obtain positional data associated with the feature of interest within the first image,

obtain a second image with the second imaging modality,

identify the feature of interest within the second image,

obtain positional data associated with the feature of interest within the second image,

combine the positional data from the first and second images, and

use the resulting data set to enable the algorithm to detect the feature of interest in at least one of the first imaging modality and the second imaging modality.

15. The system of claim 8, wherein the computer readable storage medium further comprises instructions to train the algorithm, wherein training the algorithm comprises a series of iterative steps, with successive steps evaluating new data in combination with data evaluated in previous steps.

16. A system for detecting a feature of interest in a vascular image, the

system comprising:

a processor; and

a computer readable storage medium comprising instructions that when executed cause the system to;

receive positional data from a first imaging modality and transform the positional data into a first set of coordinates, wherein the first imaging modality comprises an intravascular imaging modality associated with an intravascular device positioned within a vessel of a patient;

receive positional data from a second imaging modality and transform the positional data into a second set of coordinates, the second imaging modality being different from the first imaging modality;

create a combined data set by aligning the first set of coordinates and the second set of coordinates; and

detect a feature of interest in a vascular image based on the combined data set.

17. The system of claim 16, wherein positional data comprises data regarding the position of the feature of interest.

18. The system of claim 16, wherein the second imaging modality is selected from a group consisting of:

virtual histology intravascular ultrasound (VH-IVUS), optical coherence tomography (OCT), x-ray angiography, and magnetic resonance imaging (MRI).

19. The system of claim 16, wherein the computer readable storage medium further comprises instructions that when executed cause the system to use the combined data set to train an algorithm to detect the feature of interest.