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
1. The information disclosure statement (IDS) submitted on 02/28/2024 has been considered by the examiner.
Claim Rejections - 35 USC § 103
2. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
3. The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
4. Claim(s) 1-15 are rejected under 35 U.S.C. 103 as being unpatentable over Patterson et al., 15 June 1989, “Time resolved reflectance and transmittance for the non-invasive measurement of tissue optical properties” (pp. 2331-2336), and further in view of Utzinger et al., U.S. Patent No. 6,571,118 B1.
Regarding claim 1, Patterson discloses A method comprising: accessing, by a computing device, a model simulating light scattered by a simulated target, the model comprising a plurality of parameters (page 2331 – right column – “A simple model based on the time dependent diffusion equation is introduced which allows calculation of the pulse shape at any point on either face of the slab. The predictions of the model are shown to be in good agreement with Monte Carlo simulations performed by us and other investigators. We show that in certain conditions the absorption and scattering coefficients can be expressed as functions of simple descriptors of the pulse shape: the time of maximum signal and the decay at long times. The pulse shape recorded from the calf muscle of a human volunteer is accurately predicted by the model, and the derived absorption and scattering coefficients are similar to published values for excised muscle tissues – where absorptions and scattering coefficients are considered as a plurality of parameters);
generating, by the computing device, a set of possible histogram data using the model with a plurality of values for the parameters (as cited before in Paterson – the pulse shape recorded provides a set of possible histogram data using the model with a plurality of values for the parameters; as the pulse shape generated through the time-dependent diffusion equation is a Temporal Point Spread Function (TPSF));
Claim 1 further recites “determining, by the computing device, a set of components that represent the set of possible histogram data, the set of components having a reduced dimensionality from the set of possible histogram data”. Patterson as cited discloses generating histogram data but does not teach “determining a set of components that represent the set of possible histogram data, the set of components having a reduced dimensionality from the set of possible histogram data”. However, examiner here asserts that “determining a set of components that represent the set of possible histogram data, the set of components having a reduced dimensionality from the set of possible histogram data” is very well known in the art, and further cites Utzinger to provide evidentiary teachings. Utzinger in col. 3, lines 13-15 discloses “The apparatus may include a fiber connected from the light source to the imaging spectrograph to monitor spectral output of the light source”; further discloses in col. 4, lines 3-14 – “The step of collecting reflected light may include collecting reflected light from the sample with a reflectance collection fiber defining a collection position at about 45 degrees relative to the reflectance illumination fiber. The sample may include ovarian, head and neck, or cervical tissue. The method may also include analyzing spectral data from the detector to characterize the sample. The step of analyzing may include pre-processing the data and reducing a dimension of the data using principal component analysis. The step of analyzing may also include selecting one or more diagnostic principal components of the data and forming one or more algorithms. The step of analyzing may also include forming one or more composite algorithms. The step of analyzing may also include evaluating at least on of the algorithms using a cross-validation technique.”; further discloses in col. 4, lines 39-44 – “The invention is a method for analyzing spectroscopy data to define an optimized reduced data set. The method includes pre-processing the spectroscopy data, reducing a dimension of the spectroscopy data using principal component analysis, and selecting one or more diagnostic principal components of the spectroscopy data”. Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to use the teachings of “determining a set of components that represent the set of possible histogram data, the set of components having a reduced dimensionality from the set of possible histogram data” as taught by Utzinger in the invention of Patterson. A person having ordinary skill in the art would have been motivated before the effective filing date of the claimed invention to use the teachings of “determining a set of components that represent the set of possible histogram data, the set of components having a reduced dimensionality from the set of possible histogram data” as taught by Utzinger in the invention of Patterson, in order to reduce high-dimensional, noisy data into a few, manageable features – principal components that represent the maximum variance, preserving crucial information needed for analysis and improving signal-to-noise ratio.
Regarding claim 2, the combined invention of Patterson and Utzinger discloses “The method of claim 1, wherein the plurality of parameters comprises at least one of an absorption coefficient or a scattering coefficient of the simulated target” (see the citations made in the rejection of claim 1 with respect to Patterson in page 2331 – right column).
Regarding claim 3, the combined invention of Patterson and Utzinger discloses “The method of claim 1, wherein: the model comprises a modeled light source and a modeled detector for detecting the simulated light scattered by the simulated target; and the plurality of parameters comprises a parameter representative of a distance between the modeled light source and the modeled detector” (Patterson in page 2331 – right column - page 2331 – right column – “A simple model based on the time dependent diffusion equation is introduced which allows calculation of the pulse shape at any point on either face of the slab. The predictions of the model are shown to be in good agreement with Monte Carlo simulations performed by us and other investigators. Monte Carlo simulations as commonly well-known comprise a modeled light source (launching photons) and a modeled detector (recording photons); and, as cited absorption and scattering coefficients are fundamental, material-specific properties that determine how light intensity decreases over the distance between a light source and a detector).
Regarding claim 4, the combined invention of Patterson and Utzinger discloses “The method of claim 1, wherein the determining the set of components comprises: normalizing the set of possible histogram data to generate a normalized data set; determining a covariance of the normalized data set; and determining the set of components based on the covariance” (see Utzinger – col. 52, lines 2-49 – histogram data is normalized in pre-processing, and eigenvectors (components) of/based on the covariance are determined after pre-processing).
Regarding claim 5, the combined invention of Patterson and Utzinger discloses “The method of claim 1, wherein the components comprise eigenvectors determined using principal component analysis (PCA)” (see Utzinger – col. 52, lines 2-49 – eigenvectors (components) are determined using PCA).
Regarding claim 6, the combined invention of Patterson and Utzinger discloses “The method of claim 5, wherein the set of components comprises a subset of the eigenvectors” (see Utzinger – col. 52, lines 2-49 – subset of eigenvectors can be read on eignevectors accounting for 65, 75, 85 and 95% of total variance).
Regarding claim 7, the combined invention of Patterson and Utzinger discloses “The method of claim 1, further comprising: generating, by the computing device and based on arrival times of photons at a detector after the photons are scattered by a physical target, actual histogram data associated with the physical target; and generating, by the computing device and based on the set of components, a compressed representation of the actual histogram data.” (page 2331 – right column –We propose a practical in vivo technique in which a short light pulse is produced on the tissue surface by a small source, such as a laser beam or optical fiber, and a small detector some distance away is used to measure the time resolved pulse; further see page 2334 – left column – Topic- Materials and Methods).
Regarding claim 8, the combined invention of Patterson and Utzinger discloses “The method of claim 7, wherein the generating the compressed representation comprises determining a set of weights that define a linear combination of the set of components to represent the actual histogram data” (see Utzinger – col. 52, lines 2-49; further see Utzinger - col. 30, lines 54-57 – “ PCA was used to dimensionally reduce the pre-processed spectral data matrix into a smaller orthogonal set of linear combinations of the emission variables that account for most of the variance of the spectral data set).
Regarding claim 9, the combined invention of Patterson and Utzinger discloses “The method of claim 7, further comprising modifying, based on the actual histogram data, the set of components” (as cited in the rejection of claim 1, Utzinger teaches dimensionality reduction in PCA, where dimensionality reduction in Principal Component Analysis (PCA) modifies the set of components based on the actual data).
Regarding claim 10, claim 10 has been similarly analyzed and rejected as per citations made in the rejection of claim 1.
Regarding claim 11, claim 11 has been similarly analyzed and rejected as per citations made in the rejection of claim 2.
Regarding claim 12, claim 12 has been similarly analyzed and rejected as per citations made in the rejection of claim 3.
Regarding claim 13, claim 13 has been similarly analyzed and rejected as per citations made in the rejection of claim 4.
Regarding claim 14, claim 14 has been similarly analyzed and rejected as per citations made in the rejection of claim 5.
Regarding claim 15, claim 15 has been similarly analyzed and rejected as per citations made in the rejection of claim 6.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Manav Seth whose telephone number is (571) 272-7456. The examiner can normally be reached on Monday to Friday from 8:30 am to 5:00 pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Sumati Lefkowitz, can be reached on (571) 272-3638. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Manav Seth/
Primary Examiner, Art Unit 2672
February 15, 2026