Office Action 1: Ex Parte Quayle Action (2024-08-07)

CLAIMS:
Claims

What is claimed is:

1\. An optical coherence tomography (OCT) system for profilometry measurements of a specimen, comprising:
an interferometer configured to split incident light into a reference beam and a test beam, and to interfere the test beam reflected from the specimen with the reference beam reflected from a reference mirror to produce an interference pattern;
a spectrometer configured to analyze spectral components of the interference pattern at non-uniformly sampled wavenumbers;
a computer-readable memory configured to store a measurement model with elements connecting different depth values with different non-uniformly sampled wavenumbers and weighted with weights derived from a power spectral density (PSD) of the incident light for corresponding wavenumbers; and
a processor configured to determine the profilometry measurements of the specimen as a maximum likelihood estimate of the specimen surface depth by back-projection of the measured intensities with the measurement model.

2\. The OCT system of claim 1, wherein the depth values are uniformly sampled from a depth-measurement range with a resolution of the OCT system, and
wherein the depth values are relative values with respect to a reference depth selected outside of the depth-measurement range.
3\. The OCT system of claim 1, wherein the processor is configured to estimate 2 each profilometry measurement by executing a maximum likelihood estimator (MLE) to produce an argument of the maximum likelihood estimate of the non- zero element in the reflectivity vector corresponding, wherein each argument of the reflectivity vector corresponds to one of the depth values in the measurement model.

4\. The OCT system of claim 3, wherein the MLE is an approximate MLE, and
wherein the execution of the approximate MILE comprises back-projecting the data vector through the measurement matrix, and the MLE is the depth value corresponding to the largest-magnitude element in the back-projection.

5\. The OCT system of claim 3, wherein the MLE is an exact MLE, and wherein the execution of the exact MILE comprises refining the approximate MLE by maximizing the maximum likelihood objective function using a gradient-free optimization method.

6\. The OCT system of claim 1, wherein the spectrometer comprises:
a diffraction grating configured to diffract different beams of different wavelengths forming the interference pattern into different diffraction angles; and
a detector array with detecting elements arranged at the different diffraction angles to measure intensities of different beams corresponding to the intensities of the uniformly sampled wavelengths in the interference pattern.

7\. The OCT system of claim 6, wherein the detecting elements of the detector array are calibrated to map each index of the detecting elements in the detector array with a corresponding wavelength.
1 8. The OCT system of claim 1, wherein the incident light includes an electromagnetic two-dimensional (2D) field directed by the interferometer to form an axial scan of the specimen, such that the measured intensities of interference pattern include measurements corresponding to a sequence of points on a line of the specimen, wherein the processor is further configured to:
extract a sequence of intensities corresponding to the sequence of points; and
process the intensities of different points concurrently with each, to produce the profilometry measurements for the sequence of points.

9\. The OCT system of claim 8, further comprising:
a plurality of processing circuitry including the processor, for producing in parallel, the profilometry measurements for at least some points in the sequence of points.

10\. The OCT system of claim 8, further comprising:
an actuator to direct the incident light into another line parallel to a line of a previous scan.

11\. The OCT system of claim 1, further comprising:
an illumination source for producing the incident light, the illumination source includes one or a combination of a laser, a superluminescent diode (SLD), or a light-emitting diode (LED).

12\. The OCT system of claim 1, further comprising: a line-field generator including an extended light source of an angular size greater than a lateral resolution across the profilometry measurements, a lens arranged on a path of light emitted by the extended light source for focusing the light into an extended line-field light of a width greater than the lateral resolution, and a filter arranged in a focal plane of the lens for spatially filtering the extended line-field light into the incident light with a line-field of a width equal to the lateral resolution.

13\. The OCT system of claim 1, wherein the interferometer is a Michelson interferometer or a Linnik interferometer.

14\. The OCT system of claim 1, further comprising:
a PSD calibrator configured to block the sample arm of the interferometer so the measurement includes light only from the reference beam propagating in the reference arm of the interferometer, such that the measured intensities of the interference pattern are a function of the PSD of the incident light for corresponding wavenumbers scaled with a responsivity of the spectrometer and reflectivity of the reference arm, and wherein during execution of the PSD calibrator, the processor is configured to calibrate the PSD of the incident light such that the wavenumber corresponding to each pixel of the spectrometer is estimated.

15\. A method for profilometry measurements of a specimen in an optical coherence tomography (OCT) system, the method comprising:
splitting by an interferometer, incident light into a reference beam and a test beam, and interfering the test beam reflected from the specimen with the reference beam reflected from a reference mirror to produce an interference pattern;
analyzing by a spectrometer, spectral components of the interference pattern at non-uniformly sampled wavenumbers; wherein a computer-readable memory of the OCT system stores a 9 measurement model with elements connecting different depth values with different non-uniformly sampled wavenumbers and weighted with weights derived from a power spectral density (PSD) of the incident light for corresponding wavenumbers;
and determining the profilometry measurements of the specimen as a maximum likelihood estimate of the specimen surface depth by back-projection of the measured intensities with the measurement model.

16\. The method of claim 15, wherein the depth values are uniformly sampled from a depth-measurement range with a resolution of the OCT system, and wherein the depth values are relative values with respect to a reference depth selected outside of the depth-measurement range.

17\. The method of claim 15, further comprising estimating each profilometry measurement by executing a maximum likelihood estimator (MILE) to produce an argument of the maximum likelihood estimate of the non-zero element in the reflectivity vector corresponding, wherein each argument of the reflectivity vector corresponds to one of the depth values in the measurement model.

18\. The method of claim 17, wherein the MILE is an approximate MILE, and
wherein the execution of the approximate MILE comprises back-projecting the data vector through the measurement matrix, and the MLE is the depth value corresponding to the largest-magnitude element in the back-projection.

19\. The method of claim 17, wherein the MLE is an exact MILE, and wherein the execution of the exact MILE comprises refining the approximate MLE by maximizing the maximum likelihood objective function using a gradient-free 4 optimization method.

20\. A non-transitory computer readable medium having stored thereon computer- executable instructions which when executed by a computer, causes the computer to perform a method for profilometry measurements of a specimen in an optical coherence tomography (OCT) system, the method comprising:
splitting by an interferometer, incident light into a reference beam and a test beam, and interfering the test beam reflected from the specimen with the reference beam reflected from a reference mirror to produce an interference pattern;
analyzing by a spectrometer, spectral components of the interference pattern at non-uniformly sampled wavenumbers;
wherein a computer-readable memory of the OCT system stores a measurement model with elements connecting different depth values with different non-uniformly sampled wavenumbers and weighted with weights derived from a power spectral density (PSD) of the incident light for corresponding wavenumbers;
and determining the profilometry measurements of the specimen as a maximum likelihood estimate of the specimen surface depth by back-projection of the 17 measured intensities with the measurement model. 41 42 43 44 45 46 1 2 3 4 5 5 6 7 8 9 10 11 12 13 14 15 15 16 s

OFFICE ACTION:
DETAILED ACTION
Notice of Pre-AIA  or AIA  Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 14 September 2022 was filed in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement has been considered by the examiner. However, a copy of the reference “Profilometry with line-field Fourier-domain interferometry” which was cited on the IDS appears to be missing from the provided non-patent literature references. The examiner is furnishing a copy of the reference “Profilometry with line-field Fourier-domain interferometry”.
Specification
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
Drawings
The examiner acknowledges the drawings that were received 14 September 2022 as acceptable.
Claim Objections
Claims 1-20 are objected to because of the following informalities:
Regarding claim 1, line 15 recites “the measured intensities” which lacks antecedent basis. The examiner assumes “the measured intensities” are the result of the measurements of the spectral components of the interference pattern made by the spectrometer recited on lines 7-8. The examiner suggests amending line 15 of claim 1 to recite “back-projection of of the interference pattern with the measurement model”. Claims 2-14 depend on claim 1 and are therefore also objected to.
Further regarding claim 3, lines 3-4 recite “the non-zero element in the reflectivity vector corresponding” which lacks antecedent basis. The examiner suggests amending lines 3-4 to recite “a non-zero element in a reflectivity vector corresponding”. Claims 4-5 depend on claim 3 and are therefore also objected to.
Further regarding claim 4, lines 2-3 recite “the data vector through the measurement matrix” which lacks antecedent basis. The examiner suggests amending lines 2-3 to recite “a data vector through a measurement matrix”.
Further regarding claim 5, line 2 recites “refining the approximate MLE” which lacks antecedent basis. The examiner suggests amending line 2 to recite “an approximate MLE”.
Further regarding claim 6, lines 5-6 recite “the intensities of the uniformly sampled wavelengths” which lacks antecedent basis. The examiner suggests amending the limitation on lines 5-6 to recite “the intensities of
Further regarding claim 8, line 3 recites “the measured intensities of interference pattern” which should be amended to recite “the measured intensities of the interference pattern” to provide proper antecedence for the interference pattern.
Further regarding claim 14, line 2 recites “the sample arm of the interferometer” which should be amended to recite “a sample arm of the interferometer” to provide proper antecedence for the sample arm.
Further regarding claim 14, lines 3-4 recite “the reference arm of the interferometer” which should be amended to recite “a reference arm of the interferometer” to provide proper antecedence for the sample arm.
Regarding claim 15, lines 14-15 recite “the measured intensities” which lacks antecedent basis. The examiner assumes “the measured intensities” are the result of the measurements of the spectral components of the interference pattern made by the spectrometer recited on lines 6-7. The examiner suggests amending lines 14-15 of claim 15 to recite “back-projection of of the interference pattern with the measurement model”. Claims 16-19 depend on claim 15 and are therefore also objected to.
Further regarding claim 17, lines 3-4 recite “the non-zero element in the reflectivity vector corresponding” which lacks antecedent basis. The examiner suggests amending lines 3-4 to recite “a non-zero element in a reflectivity vector corresponding”. Claims 18-19 depend on claim 17 and are therefore also objected to.
Further regarding claim 18, lines 2-3 recite “the data vector through the measurement matrix” which lacks antecedent basis. The examiner suggests amending lines 2-3 to recite “a data vector through a measurement matrix”.
Further regarding claim 19, line 2 recites “refining the approximate MLE” which lacks antecedent basis. The examiner suggests amending line 2 to recite “an approximate MLE”.
Further regarding claim 20, lines 16-17 recite “the measured intensities” which lacks antecedent basis. The examiner assumes “the measured intensities” are the result of the measurements of the spectral components of the interference pattern made by the spectrometer recited on lines 8-9. The examiner suggests amending lines 16-17 of claim 20 to recite “back-projection of of the interference pattern with the measurement model”.
Appropriate correction is required.
Allowable Subject Matter
Claims 1-20 are allowed.
The following is an examiner’s statement of reasons for allowance:
Regarding claim 1, the prior art of record, taken alone or in combination, neither anticipates nor renders obvious an optical coherence tomography (OCT) system for profilometry measurements of a specimen, comprising: an interferometer configured to split incident light into a reference beam and a test beam, and to interfere the test beam reflected from the specimen with the reference beam reflected from a reference mirror to produce an interference pattern; a spectrometer configured to analyze spectral components of the interference pattern at non-uniformly sampled wavenumbers; a computer-readable memory configured to store a measurement model with elements connecting different depth values with different non-uniformly sampled wavenumbers and weighted with weights derived from a power spectral density (PSD) of the incident light for corresponding wavenumbers; and a processor configured to determine the profilometry measurements of the specimen as a maximum likelihood estimate of the specimen surface depth by back-projection of the measured intensities with the measurement model (emphasis added via bolded words).
Further regarding claim 1, Boppart et al. (US 2009/0185191 A1), hereinafter Boppart, teaches an OCT system for profilometry measurements of a specimen (Fig. 20(a), ¶ 0173 “A full-field OCT system, in accordance with embodiments of the present invention, is now described with reference to FIG. 20(a)”, see also ¶ 0113) which comprises an interferometer (¶ 0173 “system 1100, as shown, is based on a Michelson interferometer”) configured to split incident light into a reference beam and a test beam (Fig. 20(a) beam splitter 1114, light components 1115 and 1117), and to interfere the test beam reflected from the specimen with the reference beam reflected from a reference mirror to produce an interference pattern (Fig. 20(a) component 1115 reflects of reference mirror 1116, component 1117 is reflected off sample 8, both beams return to beam splitter 1114 which creates an interference pattern, see ¶ 0091). While Fig. 20(a) of Boppart does not teach a spectrometer, Fig. 23 teaches interfered light being directed into a spectrometer which analyzes the spectral components of the interference pattern (see ¶ 0214 and Fig. 23 spectrometer 602). While ¶ 0221 of Boppart teaches measuring non-uniform sampling of spectrum from the detector of the spectrometer, Boppart teaches the use of interpolation to account for and correct this non-uniformly sampled spectrum (see ¶ 0221, 0283-0284).
Since Boppart does not utilize the non-uniformly sampled spectrum in a measurement model, Boppart does not teach a measurement model with elements connecting different depth values with different non-uniformly sampled wavenumbers and weighted with weights derived from a power spectral density (PSD) of the incident light for corresponding wavenumbers. Furthermore, Boppart does not teach a processor configured to determine the profilometry measurements of the specimen as a maximum likelihood estimate of the specimen surface depth by back-projection of the measured intensities with the measurement model.
Wang et al. (US 2016/0213253 A1) teaches a method for the analysis of OCT images using a maximum likelihood estimation (see Wang et al. abstract and ¶ 0053), but does not teach a measurement model with elements connecting different depth values with different non-uniformly sampled wavenumbers and weighted with weights derived from a power spectral density (PSD) of the incident light for corresponding wavenumbers.
Suehira (US 2010/0027019 A1) teaches an OCT imaging method and apparatus comprising an interferometer, a spectrometer, computer-readable memory, and a processor (see Suehira Fig. 1, ¶ 0037-0040), but does not teach a measurement model with elements connecting different depth values with different non-uniformly sampled wavenumbers and weighted with weights derived from a power spectral density (PSD) of the incident light for corresponding wavenumbers.
Fercher (US 6,377,349 B1) teaches an OCT apparatus and method for surface profile measurement (see Fercher abstract) comprising an interferometer, spectrometer, memory, and processor (see Fercher Fig. 1, col. 3 line 43-col. 4 line 5). However, Fercher does not teach a measurement model with elements connecting different depth values with different non-uniformly sampled wavenumbers and weighted with weights derived from a power spectral density (PSD) of the incident light for corresponding wavenumbers.
Riza (US 7,978,346 B1) teaches a method and system for realizing 3D imaging using optical coherence tomography (see Riza abstract) which involves using iterative back-projection and maximum likelihood estimation algorithms (see Riza col. 10 lines 55-67), however, Riza does not teach a measurement model with elements connecting different depth values with different non-uniformly sampled wavenumbers and weighted with weights derived from a power spectral density (PSD) of the incident light for corresponding wavenumbers.
Izatt et al. (US 6,002,480 A) teaches an apparatus and method for depth resolved spectroscopic OCT (see Izatt et al. abstract) which involves obtaining an auto-power spectrum for an OCT system which involves using an auto-correction function having the power spectral density of a light source as a weight (see Izatt et al. col. 16 lines 41-57). However, Izatt et al. does not teach a measurement model with elements connecting different depth values with different non-uniformly sampled wavenumbers and weighted with weights derived from a power spectral density (PSD) of the incident light for corresponding wavenumbers.
Chen (WO 2014/193310 A1) teaches an optical imaging device and method using OCT (see Chen abstract and ¶ 0003-0006) comprising an interferometer and a spectrometer (see Chen Fig. 2A, the grating GR and image sensor are equivalent to a spectrometer). However, Chen does not teach a measurement model with elements connecting different depth values with different non-uniformly sampled wavenumbers and weighted with weights derived from a power spectral density (PSD) of the incident light for corresponding wavenumbers.
Huang et al. (“Maximum-likelihood estimation in Optical Coherence Tomography in the context of the tear film dynamics”) teaches the implementation of a maximum likelihood estimator to interpret OCT data based on mathematical models of Fourier-Domain OCT (see Huang et al. abstract) where the OCT system comprises an interferometer and a spectrometer (see Huang Fig. 1 and section 2. Mathematical Model of FD-OCT in the context of ML estimation). However, this model does not have elements connecting different depth values with different non-uniformly sampled wavenumbers and is not weighted with weights derived from a power spectral density (PSD) of the incident light for corresponding wavenumbers. Further, Huang et al. does not teach determine the profilometry measurements of the specimen as a maximum likelihood estimate of the specimen surface depth by back-projection of the measured intensities with the measurement model.
Kemp et al. (US 9,347,765 B2, made of record by applicant) teaches a method of processing OCT images, but does not teach, among other essential elements, a measurement model with elements connecting different depth values with different non-uniformly sampled wavenumbers and weighted with weights derived from a power spectral density (PSD) of the incident light for corresponding wavenumbers.
Further, the prior art references Suliali et al. (“Development of a low-cost 11 µm spectral domain coherence tomography surface profilometry prototype”, of record), Lawman et al. (“High precision dynamic multi-interface profilometry with optical coherence tomography”, of record), and Endo et al. (“Profilometry with line-field Fourier-domain interferometry”, provided by examiner) which are all cited by applicant in the IDS share similar teachings to the prior art references cited above by the examiner. However, these references similarly do not teach a computer-readable memory configured to store a measurement model with elements connecting different depth values with different non-uniformly sampled wavenumbers and weighted with weights derived from a power spectral density (PSD) of the incident light for corresponding wavenumbers; and a processor configured to determine the profilometry measurements of the specimen as a maximum likelihood estimate of the specimen surface depth by back-projection of the measured intensities with the measurement model (emphasis added via bolded words).
Therefore, for the reasons outlined above, claim 1 is allowed. Claims 2-14 depend on claim 1 and are therefore also allowed.
Regarding claim 15, the prior art of record, taken alone or in combination, neither anticipates nor renders obvious a method for profilometry measurements of a specimen in an optical coherence tomography (OCT) system, the method comprising: splitting by an interferometer, incident light into a reference beam and a test beam, and interfering the test beam reflected from the specimen with the reference beam reflected from a reference mirror to produce an interference pattern; analyzing by a spectrometer, spectral components of the interference pattern at non-uniformly sampled wavenumbers; wherein a computer-readable memory of the OCT system stores a measurement model with elements connecting different depth values with different non-uniformly sampled wavenumbers and weighted with weights derived from a power spectral density (PSD) of the incident light for corresponding wavenumbers; and determining the profilometry measurements of the specimen as a maximum likelihood estimate of the specimen surface depth by back-projection of the measured intensities with the measurement model (emphasis added via bolded words).
Claim 15 has similar subject matter to that of claim 1. Therefore, for the same reasons outlined above, claim 15 is allowed. Claims 16-19 depend on claim 15 and are therefore also allowed.
Regarding claim 20, the prior art of record, taken alone or in combination, neither anticipates nor renders obvious a non-transitory computer readable medium having stored thereon computer-executable instructions which when executed by a computer, causes the computer to perform a method for profilometry measurements of a specimen in an optical coherence tomography (OCT) system, the method comprising: splitting by an interferometer, incident light into a reference beam and a test beam, and interfering the test beam reflected from the specimen with the reference beam reflected from a reference mirror to produce an interference pattern; analyzing by a spectrometer, spectral components of the interference pattern at non-uniformly sampled wavenumbers; wherein a computer-readable memory of the OCT system stores a measurement model with elements connecting different depth values with different non-uniformly sampled wavenumbers and weighted with weights derived from a power spectral density (PSD) of the incident light for corresponding wavenumbers; and determining the profilometry measurements of the specimen as a maximum likelihood estimate of the specimen surface depth by back-projection of the measured intensities with the measurement model (emphasis added via bolded words).
Claim 20 has similar subject matter to that of claims 1 and 15. Therefore, for the same reasons outlined above, claim 20 is allowed.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee.  Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Conclusion
This application is in condition for allowance except for the following formal matters:
The claim objections outlined above.
Prosecution on the merits is closed in accordance with the practice under Ex parte Quayle, 25 USPQ 74, 453 O.G. 213, (Comm’r Pat. 1935).
A shortened statutory period for reply to this action is set to expire TWO (2) MONTHS from the mailing date of this letter. Extensions of time may be granted under  37 CFR 1.136 but in no case can any extension carry the date for reply to this Office action beyond the maximum period of SIX MONTHS set by statute (35 U.S.C. 133).


NEXT OFFICE ACTION: DETAILED ACTION
Notice of Pre-AIA  or AIA  Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
Applicant’s amendments, in combination with the below examiner’s amendment, filed 06 September 2024, have overcome the objections to the claims for minor informalities. The objections of the claims have been withdrawn.
EXAMINER’S AMENDMENT
An examiner’s amendment to the record appears below. Should the changes and/or additions be unacceptable to applicant, an amendment may be filed as provided by 37 CFR 1.312. To ensure consideration of such an amendment, it MUST be submitted no later than the payment of the issue fee.
Authorization for this examiner’s amendment was given in an interview with Gene Vinokur on 20 September 2024.
The application has been amended as follows:
Regarding claim 18, line 3 recites the limitation “through the measurement matrix” which has been amended to recite “through a measurement matrix” to provide proper antecedence in the claim.
Allowable Subject Matter
Claims 1-20 are allowed.
The following is an examiner’s statement of reasons for allowance:
Regarding claim 1, the prior art of record, taken alone or in combination, neither anticipates nor renders obvious an optical coherence tomography (OCT) system for profilometry measurements of a specimen, comprising: an interferometer configured to split incident light into a reference beam and a test beam, and to interfere the test beam reflected from the specimen with the reference beam reflected from a reference mirror to produce an interference pattern; a spectrometer configured to analyze spectral components of the interference pattern at non-uniformly sampled wavenumbers; a computer-readable memory configured to store a measurement model with elements connecting different depth values with different non-uniformly sampled wavenumbers and weighted with weights derived from a power spectral density (PSD) of the incident light for corresponding wavenumbers; and a processor configured to determine the profilometry measurements of the specimen as a maximum likelihood estimate of the specimen surface depth by back-projection of measured intensities of the interference pattern with the measurement model (emphasis added via bolded words).
Further regarding claim 1, see examiner’s reasons for allowance in the Ex Parte Quayle Action mailed 07 August 2024 for a further discussion on the allowability of claim 1.
Thus, claim 1 is allowed. Claims 2-14 depend on claim 1 and are therefore also allowed.
Regarding claim 15, the prior art of record, taken alone or in combination, neither anticipates nor renders obvious a method for profilometry measurements of a specimen in an optical coherence tomography (OCT) system, the method comprising: splitting by an interferometer, incident light into a reference beam and a test beam, and interfering the test beam reflected from the specimen with the reference beam reflected from a reference mirror to produce an interference pattern; analyzing by a spectrometer, spectral components of the interference pattern at non- uniformly sampled wavenumbers; wherein a computer-readable memory of the OCT system stores a measurement model with elements connecting different depth values with different non-uniformly sampled wavenumbers and weighted with weights derived from a power spectral density (PSD) of the incident light for corresponding wavenumbers; and determining the profilometry measurements of the specimen as a maximum likelihood estimate of the specimen surface depth by back-projection of measured intensities of the interference pattern with the measurement model (emphasis added via bolded words).
Further regarding claim 15, see examiner’s reasons for allowance in the Ex Parte Quayle Action mailed 07 August 2024 for a further discussion on the allowability of claim 15.
Thus, claim 15 is allowed. Claims 16-19 depend on claim 15 and are therefore also allowed.
Regarding claim 20, the prior art of record, taken alone or in combination, neither anticipates nor renders obvious a non-transitory computer readable medium having stored thereon computer-executable instructions which when executed by a computer, causes the computer to perform a method for profilometry measurements of a specimen in an optical coherence tomography (OCT) system, the method comprising: splitting by an interferometer, incident light into a reference beam and a test beam, and interfering the test beam reflected from the specimen with the reference beam reflected from a reference mirror to produce an interference pattern; analyzing by a spectrometer, spectral components of the interference pattern at non- uniformly sampled wavenumbers; wherein a computer-readable memory of the OCT system stores a measurement model with elements connecting different depth values with different non-uniformly sampled wavenumbers and weighted with weights derived from a power spectral density (PSD) of the incident light for corresponding wavenumbers; and determining the profilometry measurements of the specimen as a maximum likelihood estimate of the specimen surface depth by back-projection of measured intensities of the interference pattern with the measurement model (emphasis added via bolded words).
Further regarding claim 20, see examiner’s reasons for allowance in the Ex Parte Quayle Action mailed 07 August 2024 for a further discussion on the allowability of claim 20.
Thus, claim 20 is allowed.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee.  Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Conclusion

CITED REFERENCE SUMMARIES: Ref US20090185191A1: Claims:
A method of forming an image of ear tissue, comprising: non-invasively inserting a fiber-based device into a patient's ear canal; acquiring OCT data from ear tissue while the fiber-based device is in the ear canal; and converting the OCT data into at least one image.
non-invasively inserting a fiber-based device into a patient's ear canal;
acquiring OCT data from ear tissue while the fiber-based device is in the ear canal; and
converting the OCT data into at least one image.
The method of claim 1 further comprising performing further data analysis on the image while the fiber-based device is in the ear canal.
The method of claim 2 , wherein the further data analysis includes enhancing the image.
The method of claim 2 , wherein the further data analysis includes classifying the ear tissue imaged using the OCT data.
The method of claim 4 , wherein the OCT data is run through classification algorithms so as to classify the ear tissue imaged.
The method of claim 5 , wherein the classification algorithms analyze the OCT data and classify the ear tissue imaged using an optical property which is derived from the OCT data.
The method of claim 5 , wherein the optical property is one of a refractive index, a scattering profile, a scattering coefficient, an anisotropy factor, birefringence, a spectral shift, texture, a Doppler shift, a phase resolution, a phase-resolved Doppler measurement, a phase-resolved spectroscopic measurement, a light scattering parameter, and spectroscopic absorption.
The method of claim 1 , wherein the fiber-based device is connected with an otoscope.
The method of claim 1 , wherein the ear tissue is a biofilm.
A system for imaging ear tissue in real-time comprising: a core imaging unit which generates a low-coherence interferometry signal; and a fiber-based device connected with an otoscope, wherein the fiber-based device is in communication with and receives the low-coherence interferometry signal from the core imaging unit and sends a second signal back to the core imaging unit, wherein OCT data is generated by the core imaging unit.
a core imaging unit which generates a low-coherence interferometry signal; and
a fiber-based device connected with an otoscope, wherein the fiber-based device is in communication with and receives the low-coherence interferometry signal from the core imaging unit and sends a second signal back to the core imaging unit, wherein OCT data is generated by the core imaging unit.
The system of claim 10 , further comprising a core software unit which receives the OCT data and performs further data analysis on the OCT data.
The system of claim 11 , wherein the further data analysis includes enhancing the image.
The system of claim 10 , wherein the core software unit includes classification algorithms.
The system of claim 13 , wherein the classification algorithms analyze the OCT data and classify tissue imaged using an optical property which is derived from the OCT data.
The system of claim 10 , wherein the otoscope is a pneumatic otoscope which comprises an ear speculum connected with a head unit.
The system of claim 14 , wherein the fiber-based device is positioned to receive light which enters the ear speculum.
A method of analyzing ear tissue comprising: beginning a non-invasive procedure on a patient exposing middle ear tissue; and acquiring OCT data from the middle ear tissue.
beginning a non-invasive procedure on a patient exposing middle ear tissue; and
acquiring OCT data from the middle ear tissue.
- 24 . (canceled)
A method of examining a patient's ear, comprising: non-invasively acquiring OCT data from the patient's middle ear; and analyzing the data for the presence of a biofilm in the patient's middle ear.
non-invasively acquiring OCT data from the patient's middle ear; and
analyzing the data for the presence of a biofilm in the patient's middle ear.
A method of examining a patient's ear, comprising: non-invasively acquiring OCT data from the patient's middle ear; and analyzing the data for the patient's middle ear condition.
analyzing the data for the patient's middle ear condition.
- 29 . (canceled)
An apparatus for examining a patient's ear, comprising: (a) a core imaging unit for acquiring OCT data of a tissue, and (b) a device, adapted for selecting as the tissue the patient's middle ear, connected to the core imaging unit.
(a) a core imaging unit for acquiring OCT data of a tissue, and
(b) a device, adapted for selecting as the tissue the patient's middle ear, connected to the core imaging unit.
- 32 . (canceled)
Ref US20160213253A1: Claims:
A method comprising: storing three-dimensional image data acquired intravascularly via an optical coherence tomography (OCT) apparatus; analyzing the image data to compute a probability estimate of stent presence at support positions appearing in an A-line; and identifying stent strut locations in three-dimensional space based on the computed probability estimate of stent presence.
storing three-dimensional image data acquired intravascularly via an optical coherence tomography (OCT) apparatus;
analyzing the image data to compute a probability estimate of stent presence at support positions appearing in an A-line; and
identifying stent strut locations in three-dimensional space based on the computed probability estimate of stent presence.
The method of claim 1 , further comprising: generating a two-dimensional en face image based on the image data; segmenting the en face image to determine strut locations; and using the strut locations from the en face image to reinforce the computed probability estimate of stent presence.
generating a two-dimensional en face image based on the image data;
segmenting the en face image to determine strut locations; and
using the strut locations from the en face image to reinforce the computed probability estimate of stent presence.
The method of claim 2 , wherein the reinforcing further comprises employing a minimum spanning tree method.
The method of claim 1 , wherein the analyzing further comprises computing an initial estimate of strut depth; identify high confidence struts based on the initial estimate of strut depth; determining a refined estimate of strut depth for the high confidence struts; interpolating strut depths at other possible locations based on the refined estimate of strut depth for the high confidence struts to provide interpolated strut depth for a subset of the other possible locations; determine a final probability estimate of strut presence.
identify high confidence struts based on the initial estimate of strut depth;
determining a refined estimate of strut depth for the high confidence struts;
interpolating strut depths at other possible locations based on the refined estimate of strut depth for the high confidence struts to provide interpolated strut depth for a subset of the other possible locations;
determine a final probability estimate of strut presence.
The method of claim 1 , further comprising determining strut depth locations in the A-line.
The method of claim 5 , wherein determining the strut depth locations further comprises using a graph cut method.
The method of claim 6 , wherein determining the strut depth locations comprising concurrently localizing the strut depths based upon the image data that is acquired during a pullback of the apparatus with respect to the stent.
The method of claim 1 , further comprising computing a percentage of stent struts with tissue coverage.
The method of claim 1 , further comprising computing at least one measurement based on the identified stent strut locations.
The method of claim 9 , wherein the at least one measurement that is computed comprises at least one of a stent area, a malapposition area of the stent or a neointima area of the stent.
The method of claim 9 , wherein the at least one measurement comprises at least one of a coverage thickness for at least one strut, a malapposition distance for a pair of struts.
The method of claim 1 , further comprising: using graph search to detect the set of A-lines containing struts, and using a graph search to determine a depth location of the stent struts.
using graph search to detect the set of A-lines containing struts, and
using a graph search to determine a depth location of the stent struts.
The method of claim 1 , wherein the stent comprises a metallic stent, the method further comprising analyzing the image data to evaluate properties of the metallic stent.
The method of claim 13 , wherein the analyzing is to analyze the properties of the metallic stent relative to properties of stents with different designs and platforms.
The method of claim 1 , wherein the stent comprises a bioabsorbable stent, the method further comprising analyzing the image data to evaluate properties of the bioabsorbable stent.
The method of claim 15 , wherein the analyzing further comprises performing comparative analysis of the properties of the bioabsorbable stent relative to properties of other stents.
The method of claim 1 , wherein the OCT apparatus is one of a time-domain OCT apparatus, a spectral-domain OCT apparatus and a swept-source OCT apparatus.
The method of claim 1 , wherein the analyzing further comprises analyzing a plurality of sets of the image data, the plurality of sets of the image data being acquired for the OCT apparatus operating based on different operating and/or control parameters.
The method of claim 18 , wherein the different operating and/or control parameters comprise at least two of different rotation speed, different pullback speed, axial and transversal resolution.
An optical coherence tomography system comprising: an optical coherence tomography (OCT) apparatus to provide three-dimensional OCT image data based on images acquired by an OCT probe intravascularly; a signal processing system that includes image analysis to analyze the image data to compute a probability estimate of stent presence at support positions appearing in an A-line; and an output generator to identify stent strut locations based on the computed probability estimate of stent presence.
an optical coherence tomography (OCT) apparatus to provide three-dimensional OCT image data based on images acquired by an OCT probe intravascularly;
a signal processing system that includes image analysis to analyze the image data to compute a probability estimate of stent presence at support positions appearing in an A-line; and
an output generator to identify stent strut locations based on the computed probability estimate of stent presence.
The system of claim 20 , wherein the image analysis is programmed to reinforce the computed probability estimate of stent presence by: generating a two-dimensional en face image based on the image data; segmenting the en face image to determine strut locations; and using the determined strut locations from the en face image to reinforce the computed probability estimate of stent presence.
using the determined strut locations from the en face image to reinforce the computed probability estimate of stent presence.
The system of claim 20 , wherein the image analysis comprises a depth locator programmed to compute an initial estimate of strut depth; identify high confidence struts based on the initial estimate of strut depth; determine a refined estimate of strut depth for the high confidence struts; interpolate strut depths at other possible locations based on the refined estimate of strut depth for the high confidence struts to provide interpolated strut depth for a subset of the other possible locations; and determine a final probability estimate of strut presence.
compute an initial estimate of strut depth;
determine a refined estimate of strut depth for the high confidence struts;
interpolate strut depths at other possible locations based on the refined estimate of strut depth for the high confidence struts to provide interpolated strut depth for a subset of the other possible locations; and
The system of claim 20 , further comprising a user interface to set control parameters for the system to control at least one of a probe rotation speed, pullback speed, axial and resolution of the OCT image.
The system of claim 20 , wherein the image analysis comprises a measurement calculator programmed to compute at least one measurement that includes a stent area, a malapposition area of the stent one strut a neointima area of the stent, a coverage thickness for at least one strut or a malapposition distance for a pair of struts.
The system of claim 24 , wherein the output generator superimposes the computed measurement on a graphical image of the stent superimposed on an image of a vessel.
Ref US20100027019A1: Claims:
An optical coherence tomographic imaging method in an optical coherence tomographic imaging apparatus in which light from a light source is divided into measurement light and reference light, said measurement light is irradiated to an object to be inspected through a sample arm, and return light from said object to be inspected is guided to a detection position, and through a detection optical path, and said reference light is guided to said detection position through a reference arm, whereby a wavelength spectrum of interfering light caused by interference of said return light and said reference light both guided to said detection position, and a tomographic image of said object to be inspected is taken by a wavelength spectrum analysis unit that analyzes said wavelength spectrum, said optical coherence tomographic imaging method comprising: a wavelength spectrum acquisition step to acquire the wavelength spectrum; a wavenumber spectrum acquisition step to convert said wavelength spectrum into a wavenumber spectrum and to decrease the number of elements to provide a wavenumber spectrum of equal intervals; and a tomographic information acquisition step to acquire tomographic information of said object to be inspected from said wavenumber spectrum of equal intervals.
light from a light source is divided into measurement light and reference light,
said measurement light is irradiated to an object to be inspected through a sample arm, and return light from said object to be inspected is guided to a detection position, and through a detection optical path, and
said reference light is guided to said detection position through a reference arm,
whereby a wavelength spectrum of interfering light caused by interference of said return light and said reference light both guided to said detection position, and a tomographic image of said object to be inspected is taken by a wavelength spectrum analysis unit that analyzes said wavelength spectrum,
said optical coherence tomographic imaging method comprising:
a wavelength spectrum acquisition step to acquire the wavelength spectrum;
a wavenumber spectrum acquisition step to convert said wavelength spectrum into a wavenumber spectrum and to decrease the number of elements to provide a wavenumber spectrum of equal intervals; and
a tomographic information acquisition step to acquire tomographic information of said object to be inspected from said wavenumber spectrum of equal intervals.
The optical coherence tomographic imaging method as set forth in claim 1 , wherein in said wavenumber spectrum acquisition step, sampling points are decided in such a manner that the intervals of wavenumbers are equal to each other, and an intensity at each sampling point is obtained as an intensity at the nearest wavenumber to a wavenumber at said each sampling point in the wavenumber spectrum converted from the wavelength spectrum.
in said wavenumber spectrum acquisition step, sampling points are decided in such a manner that the intervals of wavenumbers are equal to each other, and an intensity at each sampling point is obtained as an intensity at the nearest wavenumber to a wavenumber at said each sampling point in the wavenumber spectrum converted from the wavelength spectrum.
The optical coherence tomographic imaging method as set forth in claim 1 , wherein in said wavenumber spectrum acquisition step, sampling points are decided in such a manner that the intervals of the wavenumbers become equal to each other, and an intensity at each sampling point is obtained as intensities at two nearest wavenumbers to a wavenumber at said each sampling point in the wavenumber spectrum converted from the wavelength spectrum.
in said wavenumber spectrum acquisition step, sampling points are decided in such a manner that the intervals of the wavenumbers become equal to each other, and an intensity at each sampling point is obtained as intensities at two nearest wavenumbers to a wavenumber at said each sampling point in the wavenumber spectrum converted from the wavelength spectrum.
The optical coherence tomographic imaging method as set forth in claim 1 , further comprising: a step to increase the number of elements of the acquired wavelength spectrum after said wavelength spectrum acquisition step; wherein in said wavenumber spectrum acquisition step, the wavenumber spectrum is acquired by using the wavelength spectrum of which the number of elements has been increased.
a step to increase the number of elements of the acquired wavelength spectrum after said wavelength spectrum acquisition step;
wherein in said wavenumber spectrum acquisition step, the wavenumber spectrum is acquired by using the wavelength spectrum of which the number of elements has been increased.
The optical coherence tomographic imaging method as set forth in claim 4 , wherein in said step to increase the number of elements of the wavelength spectrum, the number of elements is increased by interpolation.
in said step to increase the number of elements of the wavelength spectrum, the number of elements is increased by interpolation.
The optical coherence tomographic imaging method as set forth in claim 4 , wherein in said step to increase the number of elements of the wavelength spectrum, a Fourier transform is applied to said wavelength spectrum to obtain element S I (i), S′ I (i) is obtained in which the number of elements in S I (i) after the Fourier transformation is expanded, as shown by the following expression, and a wavelength spectrum of which the number of elements is increased by inverse Fourier transforming S′ I (i).
in said step to increase the number of elements of the wavelength spectrum, a Fourier transform is applied to said wavelength spectrum to obtain element S I (i), S′ I (i) is obtained in which the number of elements in S I (i) after the Fourier transformation is expanded, as shown by the following expression, and a wavelength spectrum of which the number of elements is increased by inverse Fourier transforming S′ I (i).
S I â² î¢ ( i ) = { S I î¢ ( i ) , 0 â¤ i â¤ N / 2 0 , N / 2 < i < M Â· N - N / 2 S I î¢ ( i - M Â· N + N ) , M Â· N - N / 2 â¤ i â¤ M Â· N - 1
where N is the number of elements of S I (i), and M is an integer of two or more.
The optical coherence tomographic imaging method as set forth in claim 1 , wherein the number of elements of the spectrum acquired in at least either of said wavelength spectrum acquisition step and said wavenumber spectrum acquisition step is a power of 2.
the number of elements of the spectrum acquired in at least either of said wavelength spectrum acquisition step and said wavenumber spectrum acquisition step is a power of 2.
The optical coherence tomographic imaging method as set forth in claim 4 , wherein the number of elements of the spectrum acquired or generated in at least either of said wavelength spectrum acquisition step, said wavenumber spectrum acquisition step and said step to increase the number of elements of the wavelength spectrum is a power of 2.
the number of elements of the spectrum acquired or generated in at least either of said wavelength spectrum acquisition step, said wavenumber spectrum acquisition step and said step to increase the number of elements of the w
[Truncated to input limit]