Signal processing for intravascular imaging

• US 10,134,132 B2
• Filed: 06/06/2017
• Issued: 11/20/2018
• Est. Priority Date: 10/07/2013
• Status: Active Grant

• Current Assignee: ACIST Medical Systems Incorporated (Bracco SPA)
• Original Assignee: ACIST Medical Systems Incorporated (Bracco SPA)
• Inventors: Lam, Duc, Reynolds, J Steve
• Primary Examiner(s): Turchen, Rochelle
• Application Number:
  US15/615,130
• Publication Number:
  US 20170301089A1
• Time in Patent Office: 532 Days
• CPC Class Codes: A61B 5/0066 Optical coherence imaging
• CPC Class Codes: A61B 5/02007 Evaluating blood vessel condition, e.g. elasticity, compliance
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 8/0891 for diagnosis of blood vessels
• 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: A61B 8/5207 involving processing of raw data to produce diagnostic data, e.g. for generating an image reconstruction G06T11/00
• CPC Class Codes: A61B 8/5269 involving detection or reduction of artifacts for image enhancement algorithms G06T5/00
• CPC Class Codes: G01S 15/8956 using frequencies at or above 20 MHz
• CPC Class Codes: G01S 15/8977 using special techniques for image reconstruction, e.g. FFT, geometrical transformations, spatial deconvolution, time deconvolution
• CPC Class Codes: G01S 7/52034 Data rate converters
• CPC Class Codes: G01S 7/52046 Techniques for image enhancement involving transmitter or receiver image enhancement by image data processing G06T5/00
• CPC Class Codes: G01S 7/52077 with means for elimination of unwanted signals, e.g. noise or interference
• CPC Class Codes: G06T 2207/30101 Blood vessel; Artery; Vein; Vascular
• CPC Class Codes: G06T 7/0012 Biomedical image inspection

Abstract

An intravascular imaging system includes a transducer capable of generating raw data representative of the structure of a patient'"'"'s vasculature. The system includes an imaging engine for receiving the raw data and generating enhanced data for presentation to a user. The imaging engine includes a coherence filter, an envelope detection module having one or more envelope detectors, and a spatial filter for processing data in various stages. Such stages of processing in the imaging engine act to reduce high frequency noise, generate low frequency data, reduce low frequency noise, and display low frequency data with an improved signal-to-noise ratio. The system can include an image generator for generating an image based on enhanced data and a display for displaying the generated image.

Claims

1. A system for producing high definition intravascular images comprising:

an intravascular imaging catheter assembly configured to generate a raw frame of imaging information that includes a raw set of vectors, with each vector of the raw set of vectors comprising a raw set of data points;

an imaging engine coupled to the intravascular imaging catheter assembly and being configured to receive the raw frame of imaging information from the intravascular imaging catheter assembly and to produce an enhanced frame of imaging information that includes an enhanced set of vectors, the imaging engine comprising;

(a) a coherence filter configured to

(i) group vectors of the raw set of vectors into raw vector groups and

(ii) generate a first set of vectors based on comparisons of data points of each raw vector group'"'"'s vectors with one another, wherein each vector of the first set of vectors

(A) is representative of the vectors of one of the raw vector groups and

(B) comprises a first set of data points, and wherein

generating the first set of vectors comprises generating, for each of the raw vector groups, two or more super vectors within the first set of vectors and associated with the raw vector group such that the first set of vectors consists of the generated super vectors,

(b) an envelope detection module comprising a plurality of envelope detectors arranged in parallel and configured to generate a second set of vectors based on comparisons of data points within each of the first set of data points with one another, wherein (i) each vector of the second set of vectors comprises a second set of data points with a smaller number of data points that are representative of the data points of the first set of data points and (ii) the second set of vectors comprises the same number of vectors as the first set of vectors,

(c) a spatial filter configured to (i) group vectors of the second set of vectors into processed vector groups and (ii) generate the enhanced set of vectors based on comparisons of data points of each processed vector group'"'"'s vectors with one another, wherein each vector of the enhanced set of vectors (A) is representative of the vectors of one of the processed vector groups and (B) comprises an enhanced set of data points, and

(d) an image generator configured to generate an image based on the enhanced frame of imaging information; and

a display coupled to the imaging engine and configured to display the image generated by the image generator.

2. The system of claim 1, wherein the coherence filter generates the first set of vectors based on comparisons of data points of each raw vector group'"'"'s vectors with one another at like radial positions.

3. The system of claim 1, wherein the spatial filter is configured to generate the enhanced set of vectors based on comparisons of data points of each processed vector group'"'"'s vectors with one another at like and near radial positions.

4. The system of claim 1, wherein the enhanced set of data points has the same number of data points as the second set of data points.

5. The system of claim 1, wherein the system is an intravascular ultrasound (IVUS) system.

6. An imaging engine configured to receive raw frames of imaging information from an intravascular imaging catheter assembly and to produce an enhanced frame of imaging information that includes an enhanced set of vectors, the imaging engine comprising:

(a) a coherence filter configured to

(i) group vectors of a raw set of vectors into raw vector groups, and

(ii) generate a first set of vectors based on comparisons of data points of each raw vector group'"'"'s vectors with one another, wherein each vector of the first set of vectors

(A) is representative of the vectors of one of the raw vector groups and

(B) comprises a first set of data points, and

wherein generating the first set of vectors comprises generating, for each of the raw vector groups, two or more super vectors within the first set of vectors and associated with the raw vector group such that the first set of vectors consists of the generated super vectors;

(b) an envelope detection module comprising a plurality of envelope detectors arranged in parallel and configured to generate a second set of vectors based on comparisons of data points within each of the first set of data points with one another, wherein (i) each vector of the second set of vectors comprises a second set of data points with a smaller number of data points that are representative of the data points of the first set of data points and (ii) the second set of vectors comprises the same number of vectors as the first set of vectors;

(c) a spatial filter configured to (i) group vectors of the second set of vectors into processed vector groups and (ii) generate the enhanced set of vectors based on comparisons of data points of each processed vector group'"'"'s vectors with one another, wherein each vector of the enhanced set of vectors (A) is representative of the vectors of one of the processed vector groups and (B) comprises an enhanced set of data points; and

(d) an image generator configured to generate an image based on the enhanced frame of imaging information.

7. The imaging engine of claim 6, wherein the coherence filter generates the first set of vectors based on comparisons of data points of each raw vector group'"'"'s vectors with one another at like radial positions.

8. The imaging engine of claim 6, wherein the enhanced set of data points has the same number of data points as the second set of data points.

9. The imaging engine of claim 6, wherein the image generated by the image generator is a high definition intravascular image generated and displayed in real time.

10. The imaging engine of claim 6, wherein the envelope detection module comprises multiple envelope detectors arranged in parallel, with each envelope detector being configured to generate a subset of the second set of vectors.

11. The imaging engine of claim 6, wherein the coherence filter is configured to generate the first set of vectors based on comparisons of data points of each raw vector group'"'"'s vectors with one another at like radial positions.

12. The imaging engine of claim 6, wherein the spatial filter is configured to generate the enhanced set of vectors based on comparisons of data points of each processed vector group'"'"'s vectors with one another at like and near radial positions.

13. A method for filtering and processing raw high frequency image information into low frequency brightness data, the method comprising:

receiving raw frames of imaging information from an intravascular imaging catheter assembly, the raw frames of imaging information including a raw set of vectors, with each vector of the raw set of vectors comprising a raw set of data points;

removing high frequency noise from the raw frames of imaging information by (i) grouping vectors of the raw set of vectors into raw vector groups and (ii) generating a first set of vectors based on comparisons of data points of each raw vector group'"'"'s vectors with one another, wherein each vector of the first set of vectors (A) is representative of the vectors of one of the raw vector groups and (B) comprises a first set of data points having the same number of data points as the raw set of data points; and

wherein

generating the first set of vectors comprises generating, for each of the raw vector group, two or more super vectors within the first set of vectors and associated with the raw vector group such that the first set of vectors consists of the generated super vectors;

converting high frequency data into low frequency brightness data by generating a second set of vectors based on comparisons of data points within each of the first set of data points with one another, wherein (i) each vector of the second set of vectors comprises a second set of data points with a smaller number of data points that are representative of the data points of the first set of data points and (ii) the second set of vectors comprises the same number of vectors as the first set of vectors;

removing low frequency noise by (i) grouping vectors of the second set of vectors into processed vector groups and (ii) generating an enhanced set of vectors based on comparisons of data points of each processed vector group'"'"'s vectors with one another, wherein each vector of the enhanced set of vectors (A) is representative of the vectors of one of the processed vector groups and (B) comprises an enhanced set of data points; and

providing the enhanced set of vectors as an enhanced frame of imaging information to an image generator for generating an image.

14. The method of claim 13, further comprising generating the image with the image generator and amplifying the image.

15. The method of claim 13, further comprising generating the image with the image generator and applying gain to the image.

16. The method of claim 13, wherein the method reduces a full frequency range of image noise including high and low frequency noise and wherein frequency ranges affected by high and low frequency noise reduction overlap at least partially.

17. The method of claim 13, wherein removing high frequency noise from the raw frames of imaging information by generating the first set of vectors is based on comparisons of data points of each raw vector group'"'"'s vectors with one another at like radial positions.

18. The method of claim 17, wherein generating the enhanced set of vectors is based on comparisons of data points of each processed vector group'"'"'s vectors with one another like and near radial positions.

19. The method of claim 13, wherein the comparisons of data points of each processed group'"'"'s vectors with one another at like and near radial positions exclude outlier data points at like and near radial positions.

20. The method of claim 13, wherein the enhanced set of data points has the same number of data points as the second set of data points.