DETAILED ACTION
The amendment and RCE filed on 03/24/2026 has been entered and fully considered. Claims 21 and 25-44 are pending, of which claims 21 and 40 are amended, and claim 44 is newly added.
Response to Amendment
In response to amendment, the examiner maintains rejection over the prior art established in the previous Office 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 .
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
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Claim 21 and 25-43 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1-17 of U.S. Patent No. 11,761,895. Although the claims at issue are not identical, they are not patentably distinct from each other because both the instant claims and the currently patented claims expressly recite the same subject matter, it would have been obvious to one of ordinary skill in the art at the time the invention was made to employ both device and methods, as recited in both sets of claims.
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 21 and 25-44 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sakai (EP 3043168, IDS) in view of Du et al. (The Open Medical Informatics Journal, 2010) (Du).
Regarding claim 21, Sakai discloses an information processing apparatus (abstract) comprising:
a fluorescence signal acquisition unit that acquires a plurality of fluorescence spectra (Fig. 3(B), par [0024]), the fluorescence stained cell being created by staining a cell with a fluorescence reagent (par [0022]);
a link unit that generates a linked fluorescence spectrum by linking at least parts of the plurality of fluorescence spectra corresponding to the excitation light to each other in a wavelength direction (prestored reference spectrum), wherein data segments of a predetermined spectral width are extracted from respective segments of the plurality of fluorescence spectra and are linked together end-to-end (with some overlap) in the wavelength direction to form the linked fluorescence spectrum (Fig. 1, par [0030]); and
a separation unit that separates the linked fluorescence spectrum into spectra for every fluorescent substance using a reference spectrum including a linked autofluorescence reference spectrum in which spectra are extracted for each of a plurality of autofluorescent substances in the cell and the obtained spectra of the plurality of autofluorescent substances in the cell are linked to each other in the wavelength direction and a linked fluorescence reference spectrum in which the spectra of the fluorescent substances in the fluorescence stained cell are linked to each other in the wavelength direction (Fig. 3(C), par [0033] [0034][0036][0038]).
When Sakai extracts data from each of prestrored reference spectra (simple staining spectra as shown in Fig. 3A), the spectral width has to be pre-determined, because the spectral width has to be wide enough to include the spectral width of the peak of interest to be extracted, and not to be so wide as to waist the storage space in computer database. Thus, a person skilled in the art would have been motivated to predetermine the spectral width of the plurality of fluorescence spectra to be extracted. Further, a computer software for the extraction would have to require a predetermined spectral width for the programming. Fig. 3C of Sakai shows that the extracted data is linked together in the wavelength direction to form the linked fluorescence spectrum.
Fig. 1 of Sakai is copied as the following:
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Sakai teaches that “In addition, in Fig. 1, the curve (the basis function) representing a simple staining spectrum of a first fluorochrome (a fluorochrome 1) is denoted as X1 (x). The curve representing a simple staining spectrum of a second fluorochrome (a fluorochrome 2) is denoted as X2(x). The curve representing a simple staining spectrum of an Mth fluorochrome (a fluorochrome M) is denoted as XM(x). A simple staining spectrum may be obtained by preparing a sample 45 labeled with one of the fluorochromes every time a measurement is conducted. Alternatively, a prestored reference spectrum may be used.” (par [0030]). Here, Sakai teaches that in Fig. 1, the segment X1(x) is the data segment of a predetermined spectral width 1, extracted from a simple staining spectrum 1; the segment X2(x) is the data segment of a predetermined spectral width 2, extracted from a simple staining spectrum 2; the segment XM(x) is the data segment of a predetermined spectral width M, extracted from a simple staining spectrum M. It is readily clear that each data segment of the predetermined width is not necessarily the same. Some data segments are overlap (e.g. X1(x) and X2(x)) and some data segments are distant from each other (e.g. X2(x) and XM(x)). The respective plurality of fluorescence spectra (simple staining spectra) are shown in Fig 3A of Sakai. Therefore, Sakai teaches a link unit that generates a linked fluorescence spectrum by linking at least parts of the plurality of fluorescence spectra corresponding to the excitation light to each other in a wavelength direction, wherein data segments of a predetermined spectral width are extracted from respective segments of the plurality of fluorescence spectra and are linked together end-to-end in the wavelength direction to form the linked fluorescence spectrum (Fig. 1, par [0030]).
Sakai does not specifically disclose a plurality of excitation lights having different wavelengths and irradiated to a fluorescence stained cell. However, since the plurality of fluorophores have absorption peaks having different wavelength, a plurality of excitation lights having different wavelengths corresponding to the wavelength of the absorption peak would generate most of the fluorescence emission intensity of the fluorophores. Du teaches that “The accurate measurement of cell and nuclei contours are critical for the sensitive and specific detection of changes in normal cells in several medical informatics disciplines. Within microscopy, this task is facilitated using fluorescence cell stains, and segmentation is often the first step in such approaches.” (abstract). Thus, it would have been obvious to one of ordinary skill in the art to use a plurality of excitation lights having different wavelengths and irradiated to a fluorescence stained cell labeled with plurality of fluorophores, in order to obtain the most of the fluorescence emission intensity.
Sakai does not explicitly disclose generating image information including segmentation and visualization outputs.
However, Du teaches:
segmentation of fluorescence microscopy images (abstract), and
generation of processed image outputs for analysis:
“segmentation … is often the first step” and segmented images are generated and evaluated (abstract).
Thus, Du teaches generating image information based on fluorescence data.
Sakai teaches computing fluorescence intensities/spectra for individual fluorochromes based on spectral decomposition (see above).
Sakai explicitly teaches:
“autofluorescence spectrum” used in decomposition of measured spectra (par [0033] [0034][0036][0038]).
Du teaches segmentation of cell images (abstract), which inherently identifies regions corresponding to individual cells or subregions within an image, i.e., regions of interest.
Du explicitly teaches segmentation of fluorescence cell images and generation of segmentation results (abstract).
Du teaches evaluation metrics (e.g., precision, recall, F-score) for segmented images, which are measures of signal quality and performance, corresponding to signal-to-noise or quality metrics associated with processed fluorescence data (page 44, par 2).
It would have been obvious to one of ordinary skill in the art at the time of the invention to modify Sakai’s fluorescence analysis system to include the image processing and segmentation techniques taught by Du, in order to improve interpretation and visualization of fluorescence data, provide meaningful image-based outputs (e.g., segmented cells), and enhance analysis of fluorescence microscopy data.
Both references are directed to fluorescence-based analysis of cells, and their combination represents the use of known techniques (spectral decomposition and image segmentation) according to their established functions to yield predictable results.
Regarding claim 25, Sakai discloses that wherein the separation unit separates the linked fluorescence spectrum into the spectra for every fluorescent substance using any one of a least square method or a weighted least square method using the reference spectrum (par [0042]).
Regarding claim 26, Sakai discloses that wherein the separation unit separates the linked fluorescence spectrum into the spectra for every fluorescent substance by setting a matrix representing the linked fluorescence spectrum as Signal (yi), setting a matrix representing the reference spectrum as St (X), setting a matrix representing a color mixture rate of each of the reference spectra in the linked fluorescence spectrum as a, and calculating the matrix a (a) representing the color mixture rate when a sum of squares of values represented by the following Equation (1) becomes minimum (Eq. 2, par [0042]).
Regarding claim 27, Sakai discloses that wherein the separation unit separates the linked fluorescence spectrum into the spectra for every fluorescent substance using the reference spectrum including the linked autofluorescence reference spectrum and the linked fluorescence reference spectrum, which are calculated on a basis of the number of fluorescent molecules or the number of antibodies bound to the fluorescent molecules, or the reference spectrum including the linked autofluorescence reference spectrum and the linked fluorescence reference spectrum for each of the fluorescent molecules or for each of the antibodies (par [0031] [0042]).
Regarding claim 28, Sakai discloses that wherein the separation unit separates the linked fluorescence spectrum into the spectra for every fluorescent substance by performing non-negative matrix factorization on the linked fluorescence spectra (par [0038]).
Regarding claim 29, Sakai discloses that wherein the separation unit specifies a correspondence between the fluorescent substance and the extracted spectrum by calculating a product moment correlation coefficient with an initial value used for the non- negative matrix factorization for a spectrum extracted by the nonnegative matrix factorization (par [0038][0042]).
Regarding claim 30, Sakai discloses that wherein the link unit corrects the plurality of fluorescence spectra, and links at least parts of the plurality of fluorescence spectra after being corrected to each other in the wavelength direction (an i-th photodetector) (par [0042][0043]).
Regarding claim 31, Sakai discloses that wherein the link unit corrects intensities of the plurality of fluorescence spectra (par [0042][0043]).
Regarding claim 32, it is conventional to correct the intensities of the plurality of fluorescence spectra by dividing the plurality of fluorescence spectra by an excitation power density, because the intensity of fluorescence is positively related to the excitation power density.
Regarding claim 33, it is conventional to correct a wavelength resolution of at least one of the plurality of fluorescence spectra to a wavelength resolution different from a wavelength resolution of another fluorescence spectrum for comparison purpose.
Regarding claim 34, Sakai discloses that wherein the link unit extracts fluorescence spectra in wavelength bands including intensity peaks from each of the plurality of fluorescence spectra, and generates the linked fluorescence spectrum by linking the extracted fluorescence spectra to each other (par [0042]).
Regarding claim 35, Sakai discloses that wherein the linked fluorescence spectrum is discontinuously linked in the wavelength direction among the plurality of fluorescence spectra (Fig. 3(A)(B)).
Regarding claim 36, Sakai discloses that wherein the fluorescence signal acquisition unit acquires first image data which is obtained by imaging the fluorescence stained cell and includes the plurality of fluorescence spectra (Fig. 3(A)(B), par [0042]), and
the separation unit separates the first image data into the spectra for every fluorescent substance by performing non-negative matrix factorization on a first Gram matrix of the first image data (par [0038][0042]).
Regarding claim 37, Sakai discloses that wherein the separation unit calculates the first Gram matrix by convolving a second Gram matrix of each of a plurality of second image data obtained by dividing the first image data (par [0043][0046]).
Regarding claim 38, Sakai discloses that wherein the fluorescence signal acquisition unit acquires first image data by imaging the cell that is nonstained and irradiated with the excitation light (par [0033]), and
an extraction unit extracts the spectra for every autofluorescent substance from the first image data by performing non-negative matrix factorization on a first Gram matrix of the first image data, and updates the linked autofluorescence reference spectrum using the extracted spectra for every autofluorescent substance (par [0038][0042][0046]).
Regarding claim 39, Sakai does not specifically disclose that wherein wavelengths at boundaries between the linked together data segments are not continuous. However, a person skilled in the art would have recognized that for Sakai’s algorithm of summarize wavelength fluorescence spectra to fit a measured spectrum, the key is to identify the important peaks in the fluorescence spectrum and use a suitable curve fitting algorithm to extract the underlying patterns and fit it to the measured spectrum. Therefore, whether wavelengths at boundaries between the linked together data segments are continuous or not is irrelevant.
Regarding claim 40, Sakai discloses a microscope system comprising:
a light source that irradiates a fluorescence stained cell with an excitation light (par [0054]), the fluorescence stained cell being created by staining a cell with a fluorescence reagent (par [0022]);
an imaging apparatus that acquires a plurality of fluorescence spectra corresponding to the excitation light (par [0054]); and
a non-transitory computer readable medium storing instructions that, when executed by processing circuitry, perform a process using the plurality of fluorescence spectra (par [0056]), the process comprising:
generating a linked fluorescence spectrum by linking at least parts of the plurality of fluorescence spectra corresponding to the excitation light to each other in a wavelength direction, wherein data segments of a predetermined spectral width are extracted from respective segments of the plurality of fluorescence spectra (simple staining spectra as shown in Fig. 3A) and are linked together end-to-end in the wavelength direction to form the linked fluorescence spectrum (Fig. 1, par [0030]); and
separating the linked fluorescence spectrum into spectra for every fluorescent substance using a reference spectrum including a linked autofluorescence reference spectrum in which spectra of autofluorescent substances in the cell are linked to each other in the wavelength direction and a linked fluorescence reference spectrum in which the spectra of the fluorescent substances in the fluorescence stained cell are linked to each other in the wavelength direction (Fig. 3(C), par [0042][0047]).
When Sakai extracts data from each of prestrored reference spectra (simple staining spectra as shown in Fig. 3A), the spectral width has to be pre-determined, because the spectral width has to be wide enough to include the spectral width of the peak of interest to be extracted, and not to be so wide as to waist the storage space in computer database. Thus, a person skilled in the art would have been motivated to predetermine the spectral width of the plurality of fluorescence spectra to be extracted. Further, a computer software for the extraction would have to require a predetermined spectral width for the programming. Fig. 3C of Sakai shows that the extracted data is linked together in the wavelength direction to form the linked fluorescence spectrum.
Fig. 1 of Sakai is copied as the following:
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Sakai teaches that “In addition, in Fig. 1, the curve (the basis function) representing a simple staining spectrum of a first fluorochrome (a fluorochrome 1) is denoted as X1 (x). The curve representing a simple staining spectrum of a second fluorochrome (a fluorochrome 2) is denoted as X2(x). The curve representing a simple staining spectrum of an Mth fluorochrome (a fluorochrome M) is denoted as XM(x). A simple staining spectrum may be obtained by preparing a sample 45 labeled with one of the fluorochromes every time a measurement is conducted. Alternatively, a prestored reference spectrum may be used.” (par [0030]). Here, Sakai teaches that in Fig. 1, the segment X1(x) is the data segment of a predetermined spectral width 1, extracted from a simple staining spectrum 1; the segment X2(x) is the data segment of a predetermined spectral width 2, extracted from a simple staining spectrum 2; the segment XM(x) is the data segment of a predetermined spectral width M, extracted from a simple staining spectrum M. It is readily clear that each data segment of the predetermined width is not necessarily the same. Some data segments are overlap (e.g. X1(x) and X2(x)) and some data segments are distant from each other (e.g. X2(x) and XM(x)). The respective plurality of fluorescence spectra (simple staining spectra) are shown in Fig 3A of Sakai. Therefore, Sakai teaches generating a linked fluorescence spectrum by linking at least parts of the plurality of fluorescence spectra corresponding to the excitation light to each other in a wavelength direction, wherein data segments of a predetermined spectral width are extracted from respective segments of the plurality of fluorescence spectra (simple staining spectra as shown in Fig. 3A) and are linked together end-to-end in the wavelength direction to form the linked fluorescence spectrum (Fig. 1, par [0030]).
Sakai teaches that “However, the intensity and the pattern of autofluorescence vary from subpopulation to subpopulation. Accordingly, the computation in which the same average value is subtracted from each of all of the populations causes an error in the computation value of the fluorescence intensity. In particular, if a variation in autofluorescence among subpopulations to be analyzed is significant, the error increases.” (par [0008]). “In computing fluorescence intensities, the fluorescence intensity of each of the fluorochromes and the autofluorescence intensity can be computed by approximating a measured spectrum obtained by collecting detection values of the photodetectors with a linear sum of a simple staining spectrum obtained from the microparticle labeled with one of the fluorochromes and an autofluorescence spectrum obtained from the micro particle that is not labeled with any one of the fluorochromes. By performing computation while taking into account the autofluorescence component of the microparticle, the autofluorescence component that varies from subpopulation to subpopulation can be accurately computed and, therefore, the occurrence of a measurement error caused by a variation in the autofluorescence intensity from subpopulation to subpopulation can be prevented” (par [0012]).” Here, Sakai teaches that because the autofluorescence vary from subpopulation to subpopulation, each autofluorescence has to be computed.
Again, Sakai does not specifically disclose a plurality of excitation lights having different wavelengths and acquires a plurality of fluorescence spectra corresponding to each of the plurality of excitation lights. However, since the plurality of fluorophores have absorption peaks having different wavelength, a plurality of excitation lights having different wavelengths corresponding to the wavelength of the absorption peak would generate most of the fluorescence emission intensity of the fluorophores. Thus, it would have been obvious to one of ordinary skill in the art to use a plurality of excitation lights having different wavelengths and acquires a plurality of fluorescence spectra corresponding to each of the plurality of excitation lights, in order to obtain the most of the fluorescence emission intensity.
Sakai does not explicitly disclose generating image information including segmentation and visualization outputs.
However, Du teaches:
segmentation of fluorescence microscopy images (abstract), and
generation of processed image outputs for analysis:
“segmentation … is often the first step” and segmented images are generated and evaluated (abstract).
Thus, Du teaches generating image information based on fluorescence data.
Sakai teaches computing fluorescence intensities/spectra for individual fluorochromes based on spectral decomposition (see above).
Sakai explicitly teaches:
“autofluorescence spectrum” used in decomposition of measured spectra (par [0033] [0034][0036][0038]).
Du teaches segmentation of cell images (abstract), which inherently identifies regions corresponding to individual cells or subregions within an image, i.e., regions of interest.
Du explicitly teaches segmentation of fluorescence cell images and generation of segmentation results (abstract).
Du teaches evaluation metrics (e.g., precision, recall, F-score) for segmented images, which are measures of signal quality and performance, corresponding to signal-to-noise or quality metrics associated with processed fluorescence data (page 44, par 2).
It would have been obvious to one of ordinary skill in the art at the time of the invention to modify Sakai’s fluorescence analysis system to include the image processing and segmentation techniques taught by Du, in order to improve interpretation and visualization of fluorescence data, provide meaningful image-based outputs (e.g., segmented cells), and enhance analysis of fluorescence microscopy data.
Both references are directed to fluorescence-based analysis of cells, and their combination represents the use of known techniques (spectral decomposition and image segmentation) according to their established functions to yield predictable results.
Regarding claim 41 and 43, Fig. 1 of Sakai shows that wherein data segments (e.g. X1(x), X2(x), XM(x)) of a predetermined spectral width have a spectral resolution that is the same or different as other linked data segments, and have wavelength values at the boundaries with adjacent linked data segments that are continuous or non-continuous.
Regarding claim 42, Sakai discloses that wherein an extraction unit updates the linked autofluorescence reference spectrum using the spectra for every fluorescent substance separated by the separation unit (par [0008][0012]).
Regarding claim 44, Sakai discloses an information processing apparatus (abstract) comprising:
a fluorescence signal acquisition unit that acquires a plurality of fluorescence spectra corresponding to excitation light irradiated to a fluorescence-stained cell (Fig. 3B, par [0022][0024]);
a link unit that generates a linked fluorescence spectrum by linking at least parts of the plurality of fluorescence spectra to each other in a wavelength direction (Fig. 1, par [0030]); and
a separation unit that separates the linked fluorescence spectrum into spectra for every fluorescent substance using a reference spectrum including a linked autofluorescence reference spectrum in which spectra of autofluorescent substances in the cell are linked to each other in the wavelength direction and a linked fluorescence reference spectrum in which the spectra of the fluorescent substances in the fluorescence stained cell are linked to each other in the wavelength direction (Fig. 3C, par [0033][0034][0036][0038]).
Sakai does not specifically disclose a plurality of excitation lights having different wavelengths and irradiated to a fluorescence stained cell. However, since the plurality of fluorophores have absorption peaks having different wavelength, a plurality of excitation lights having different wavelengths corresponding to the wavelength of the absorption peak would generate most of the fluorescence emission intensity of the fluorophores. Du teaches that “The accurate measurement of cell and nuclei contours are critical for the sensitive and specific detection of changes in normal cells in several medical informatics disciplines. Within microscopy, this task is facilitated using fluorescence cell stains, and segmentation is often the first step in such approaches.” (abstract). Thus, it would have been obvious to one of ordinary skill in the art to use a plurality of excitation lights having different wavelengths and irradiated to a fluorescence stained cell labeled with plurality of fluorophores, in order to obtain the most of the fluorescence emission intensity.
Response to Arguments
Applicant's arguments filed 03/24/2026 have been fully considered but they are not persuasive.
Applicant argues that Sakai does not teach:
“linking at least parts of the plurality of fluorescence spectra to each other in a wavelength direction” and instead only discloses overlapping spectra
This argument is not persuasive.
Sakai explicitly teaches constructing a measured spectrum from detection values obtained from a plurality of photodetectors having different wavelength ranges (Fig. 3B, par [0024]). As described in Sakai:
detection values from multiple photodetectors are collected across wavelength ranges (Fig. 3B, par [0024]), and
the measured spectrum is treated as a combined spectral representation used for subsequent processing (e.g., least squares fitting, matrix operations) (Fig. 1, par [0030][0031]).
In particular, Sakai describes that:
the measured spectrum is approximated as a linear sum of basis spectra corresponding to fluorochromes and autofluorescence (see Sakai, e.g., par [0027]-[0031]).
This necessarily requires that spectral data from multiple wavelength regions be combined into a single representation spanning wavelength, which corresponds to the claimed “linked fluorescence spectrum.”
Applicant’s argument improperly attempts to limit “linking” to a specific end-to-end, non-overlapping concatenation format (as illustrated in Applicant’s Fig. 6).
However, the claims do not require:
non-overlapping segments,
discontinuities, or
any specific data structure beyond “linking … in a wavelength direction.”
Sakai’s construction of a measured spectrum from multiple wavelength-dependent detection values reasonably meets this limitation under the broadest reasonable interpretation (BRI).
Applicant further argues that:
“No combination of Sakai or Du teaches or suggests that the spectra … are linked to each other in the wavelength direction”
This argument is also not persuasive.
Sakai expressly teaches modeling fluorescence signals as a linear combination of multiple spectral components, including:
spectra of individual fluorochromes, and
autofluorescence spectra (Fig. 3C, par [0033][0034][0036][0038]).
These spectra are represented as vectors spanning wavelength space and are used together in matrix-based computations (e.g., least squares fitting) (par [0043]).
Thus, Sakai inherently utilizes reference spectra that span wavelength and are used collectively, which corresponds to the claimed “linked … reference spectrum.”
Again, Applicant’s argument relies on a narrow interpretation requiring a specific concatenation scheme, which is not recited in the claims.
Applicant argues that Du does not disclose an “image generation unit” and only describes algorithms:
“Du does not discuss specific device implementations or components”
This argument is not persuasive.
Du clearly teaches:
segmentation of fluorescence microscopy images, and
generation and evaluation of segmented image outputs (abstract).
As stated in Du:
segmentation is performed to produce segmented cell images for analysis and evaluation (abstract)
The generation of segmented images constitutes image information output, which corresponds to the claimed “image generation unit.”
Under well-established precedent, recitation of a “unit” does not require a specific structural implementation and may be satisfied by software, algorithms, or processing functionality.
Furthermore, it would have been obvious to one of ordinary skill in the art to implement Du’s segmentation techniques within Sakai’s fluorescence analysis system in order to:
improve visualization and interpretation of fluorescence data, and
provide meaningful image-based outputs for users.
Applicant further argues that the cited art does not teach generating image information including:
fluorescence spectrum
autofluorescence spectrum
region of interest
segmentation result
signal-to-noise ratio
This argument is not persuasive.
Sakai teaches:
computation of fluorescence intensities and spectra from detection data, and
use of mathematical processing (e.g., least squares) on spectral data (Fig. 3C, par [0033][0034][0036][0038]).
Du teaches:
segmentation of cell images, and
generation of processed image outputs for analysis (abstract).
It would have been obvious to one of ordinary skill in the art to:
display or otherwise generate image information reflecting computed spectral data (from Sakai), and
include segmentation results and related metrics (from Du), including regions of interest and quality measures (e.g., signal-to-noise),
as such outputs represent routine visualization and analysis of processed data.
The combination merely involves using known data outputs (spectra, segmentation, metrics) in a predictable manner to provide useful image information to a user.
Applicant asserts that the cited art does not teach the limitations “in the ordered combination.”
This argument is not persuasive.
The rejection relies on a combination of Sakai and Du, where:
Sakai provides the fluorescence acquisition and spectral processing framework (Fig. 3C, par [0033][0034][0036][0038]). and
Du provides image segmentation and output techniques (abstract).
The combination of these teachings yields the claimed invention in a predictable manner, consistent with KSR.
Applicant has not identified any critical or non-obvious interaction between the claimed elements that would distinguish over the combined teachings.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to XIAOYUN R XU, Ph. D. whose telephone number is (571)270-5560. The examiner can normally be reached M-F 8am-5pm.
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/XIAOYUN R XU, Ph.D./Primary Examiner, Art Unit 1797
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