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 .
Clarity of the Record - Claim Interpretation
The white blood cell morphological features in claims 1, 14 and 20 as well as the stains of claim 6 are claimed in the alternative, based on the use of the term ‘or’ in the claim limitations.
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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Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-14 and 16-20 of U.S. Patent No. 12272061. Although the claims at issue are not identical, they are not patentably distinct from each other because the scope of the previously claimed limitations encompasses or renders obvious the scope of the currently claimed limitations.
Claim 1 is encompassed by 1 of the ‘061 Patent
Claim 2 is encompassed by 2 of the ‘061 Patent
Claim 3 is encompassed by 3 of the ‘061 Patent
Claim 4 is encompassed by 4 of the ‘061 Patent
Claim 5 is encompassed by 5 of the ‘061 Patent
Claim 6 is encompassed by 6 of the ‘061 Patent
Claim 7 is encompassed by 7 of the ‘061 Patent
Claim 8 is encompassed by 8 of the ‘061 Patent
Claim 9 is encompassed by 9 of the ‘061 Patent
Claim 10 is encompassed by 10 of the ‘061 Patent
Claim 11 is encompassed by 11 of the ‘061 Patent
Claim 12 is encompassed by 12 of the ‘061 Patent
Claim 13 is encompassed by 13 of the ‘061 Patent
Claim 14 is encompassed by 14 of the ‘061 Patent
Claim 15 is encompassed by 16 of the ‘061 Patent
Claim 16 is encompassed by 4 of the ‘061 Patent
The encompassing disclosure of claim 4 from the ‘061 patent is obvious in view of the scope of current claim 16, as claim 4 recites the obviously associated method to the apparatus of claim 16. It would be obvious to one of skill in the art to associate the method and apparatus disclosures as the method discloses the desired functional output of the claimed apparatus and any additional scope in the way of processors would be considered common place and expected functional technology within the given field of use for the method, thereby allowing for the physical implementation of the desired functional method operations.
Claim 17 is encompassed by 17 of the ‘061 Patent
Claim 18 is encompassed by 18 of the ‘061 Patent
Claim 19 is encompassed by 19 of the ‘061 Patent
Claim 20 is encompassed by 20 of the ‘061 Patent
Claim Rejections - 35 USC § 103
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.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-3, 5-8, 13-15 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Mundhra (herein after Mun)(NPL “Analyzing Microscopic Images of Peripheral Blood Smear Using Deep Learning”, see IDS) in view of Hayut (US Pub 20190384962).
Re claim 1, Mun discloses an image analysis method comprising:
inputting analysis data (Section 2 – blood smears for analysis) into a classifier (Sections 3, 3.1 and 3.2 – use of CNN in WBC related classification) having a neural network structure (Sections 3, 3.1 and 3.2 – WBC related classification), the analysis data being generated from an image of an analysis target cell (Section 3.1 ‘Extraction of WBCs and Platelets’; Fig 2; Section 3.2 ‘Cell Classification’) and including information regarding the analysis target cell (Section 3.1 ‘Extraction of WBCs and Platelets’; Fig 2; Section 3.2 ‘Cell Classification’); and
classifying, by use of the classifier, the analysis target cell into at least one of categories of a blood cell (Section 3.1 ‘Extraction of WBCs and Platelets’; Fig 2; Section 3.2 ‘Cell Classification’; Section 4 Table 1 for WBC); Mun fails however to explicitly disclose (1) wherein the categories include morphological features of white blood cells, and (2) wherein the morphological features of white blood cells include at least morphological nucleus abnormality, presence of vacuole, granule morphological abnormality, granule distribution abnormality, presence of abnormal granule, cell size abnormality, presence of inclusion body, or bare nucleus.
Regarding items (1) and (2) above, this design is however disclosed by Hayut. Hayut discloses (1) wherein the categories include morphological features of white blood cells (Par 36, 61, 77), and (2) wherein the morphological features of white blood cells (Par 36, 61, 77) include at least morphological nucleus abnormality, presence of vacuole (Par 36, 61, 77), granule morphological abnormality, granule distribution abnormality, presence of abnormal granule, cell size abnormality, presence of inclusion body, or bare nucleus.
Therefore, it would have been obvious to one of ordinary skill in the art at the effective filing date of the invention to modify the disclosure of Mun in order to incorporate the morphological feature analysis of Hayut based on the rationale of the use of known techniques to improve similar designs in the same way, in this instance by allowing for the determination and consideration of features of the cell under analysis the preformed categorization of the cells under review can more accurately reflect their current condition and provide a more efficient diagnostic process.
Re claims 14 and 20, Mun discloses an image analysis apparatus and associated embodiment comprising:
input analysis data (Section 2 – blood smears for analysis) into a classifier (Sections 3, 3.1 and 3.2 – use of CNN in WBC related classification) having a neural network structure (Sections 3, 3.1 and 3.2 – WBC related classification), the analysis data being generated from an image of an analysis target cell (Section 3.1 ‘Extraction of WBCs and Platelets’; Fig 2; Section 3.2 ‘Cell Classification’) and including information regarding the analysis target cell (Section 3.1 ‘Extraction of WBCs and Platelets’; Fig 2; Section 3.2 ‘Cell Classification’); and
classify, by use of the classifier, the analysis target cell into at least one of categories of a blood cell (Section 3.1 ‘Extraction of WBCs and Platelets’; Fig 2; Section 3.2 ‘Cell Classification’; Section 4 Table 1 for WBC); Mun fails however to explicitly disclose (1) wherein the categories include morphological features of white blood cells, and (2) wherein the morphological features of white blood cells include at least morphological nucleus abnormality, presence of vacuole, granule morphological abnormality, granule distribution abnormality, presence of abnormal granule, cell size abnormality, presence of inclusion body, or bare nucleus; (3) wherein the apparatus comprises a processor; and (4) wherein the embodiment comprises a non-transitory computer readable medium storing programs executable by a processor.
Regarding items (1), (2), (3) and (4) above, this design is however disclosed by Hayut. Hayut discloses (1) wherein the categories include morphological features of white blood cells (Par 36, 61, 77), and (2) wherein the morphological features of white blood cells (Par 36, 61, 77) include at least morphological nucleus abnormality, presence of vacuole (Par 36, 61, 77), granule morphological abnormality, granule distribution abnormality, presence of abnormal granule, cell size abnormality, presence of inclusion body, or bare nucleus; (3) wherein the apparatus comprises a processor (Par 38, 47-48, 81-85, 87-90); and (4) wherein the embodiment comprises a non-transitory computer readable medium (Par 38, 47-48, 81-85, 87-90) storing programs (Par 38, 47-48, 81-85, 87-90) executable by a processor (Par 38, 47-48, 81-85, 87-90).
Therefore, it would have been obvious to one of ordinary skill in the art at the effective filing date of the invention to modify the disclosure of Mun in order to incorporate the morphological feature analysis of Hayut based on the rationale of the use of known techniques to improve similar designs in the same way, in this instance by allowing for the determination and consideration of features of the cell under analysis the preformed categorization of the cells under review can more accurately reflect their current condition and provide a more efficient diagnostic process.
Re claim 2, the combined disclosure of Mun and Hayut as a whole discloses the image analysis method of claim 1, and Hayut further discloses further comprising outputting the classified category of the analysis target cell (Fig 1 el 112; Par 36, 43, 50).
Re claim 3, the combined disclosure of Mun and Hayut as a whole discloses the image analysis method of claim 2, and Hayut further discloses further comprising receiving a user's modification of the outputted category (Par 39 – user verify).
Re claim 5, the combined disclosure of Mun and Hayut as a whole discloses the image analysis method of claim 1, and Mun further discloses wherein the analysis target cell in the image has been stained (Section 3.1 ‘Extraction’).
Re claim 6, the combined disclosure of Mun and Hayut as a whole discloses the image analysis method of claim 5, and Mun further discloses wherein the analysis target cell has been stained by Wright's staining, Giemsa staining (Section 4), Wright-Giemsa staining, or May-Giemsa staining (Section 4).
Re claim 7, the combined disclosure of Mun and Hayut as a whole discloses the image analysis method of claim 1, and Mun further discloses wherein the analysis target cell is contained in a peripheral blood (Section 1; PBS).
Re claim 8, the combined disclosure of Mun and Hayut as a whole discloses the image analysis method of claim 1, and Hayut further discloses further comprising: obtaining a plurality of the images of the analysis target cell from a blood smear preparation (Par 53, 75, 77); and generating the analysis data for each of the plurality of the images (Fig 1 el 112; Par 36, 43, 50, 75, 77, 79-80).
Re claim 13, the combined disclosure of Mun and Hayut as a whole discloses the image analysis method of claim 1, and Mun further discloses wherein the categories further include morphological features of platelets (Section 4 Table 3; Section 1, 3.1 and 3.2 regarding platelets).
Re claim 15, the combined disclosure of Mun and Hayut as a whole discloses the image analysis apparatus of claim 14, and Hayut further discloses wherein the image analysis apparatus (Fig 1; Par 43-44, 47-48, 50) is connected to a computer (Fig 1; Par 43-44, 47-48, 50) via a network (Fig 1; Par 43-44, 47-48, 50), wherein the computer (Fig 1; Par 43-44, 47-48, 50) is linked with an imaging apparatus configured to capture the image of the analysis target cell (Fig 1; Par 43-44, 47-48, 50), and the processor is configured to: receive the image of the analysis target cell from the computer via the network (Fig 1; Par 43-44, 47-48, 50); input the analysis data, generated from the received image of the analysis target cell, into the classifier (Fig 1; Par 43-44, 47-48, 50); classify, by use of the classifier (Par 36, 61, 77), the analysis target cell into at least one of the categories (Par 36, 61, 77); and transmit the classified category to the computer via the network (Fig 1; Par 43-44, 47-48, 50).
Re claim 19, the combined disclosure of Mun and Hayut as a whole discloses the image analysis apparatus of claim 14, and Mun further discloses wherein the categories further include morphological features of platelets (Section 4 Table 3; Section 1, 3.1 and 3.2 regarding platelets).
Claims 4 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Mun and Hayut as applied to claims 1 and 14 above, and further in view of Ando (US Patent 10134131, see IDS).
Re claim 4, the combined disclosure of Mun and Hayut as a whole discloses the image analysis method of claim 1, but fails however to explicitly disclose further comprising trimming the image of the analysis target cell so that some other cells other than the analysis target cell are removed from the image before inputting the analysis data into the classifier.
This design is however disclosed by Ando. Ando discloses further comprising trimming the image of the analysis target cell (Fig 5c/5d; Col. 7 lies 7-30; Col. 16 line 52-Col. 17 line 67) so that some other cells other than the analysis target cell are removed from the image (Fig 5c/5d; Col. 7 lies 7-30; Col. 16 line 52-Col. 17 line 67) before inputting the analysis data into the classifier (Fig 5c/5d; Col. 7 lies 7-30; Col. 16 line 52-Col. 17 line 67).
Therefore, it would have been obvious to one of ordinary skill in the art at the effective filing date of the invention to modify the disclosure of Mun in order to incorporate the image processing of Ando based on the rationale of the use of known techniques to improve similar designs in the same way, in this instance to reduce the computational complexity of the image analysis and allow for a focused and efficient processing of the targeted image areas.
Re claim 16, the combined disclosure of Mun and Hayut as a whole discloses the image analysis apparatus of claim 14, but fails however to explicitly disclose wherein the processor is configured to trim the image of the analysis target cell so that some other cells other than the analysis target cell are removed from the image before inputting the analysis data into the classifier.
This design is however disclosed by Ando. Ando discloses wherein the processor is configured to trim the image of the analysis target cell (Fig 5c/5d; Col. 7 lies 7-30; Col. 16 line 52-Col. 17 line 67) so that some other cells other than the analysis target cell are removed from the image (Fig 5c/5d; Col. 7 lies 7-30; Col. 16 line 52-Col. 17 line 67) before inputting the analysis data into the classifier (Fig 5c/5d; Col. 7 lies 7-30; Col. 16 line 52-Col. 17 line 67).
Therefore, it would have been obvious to one of ordinary skill in the art at the effective filing date of the invention to modify the disclosure of Mun in order to incorporate the image processing of Ando based on the rationale of the use of known techniques to improve similar designs in the same way, in this instance to reduce the computational complexity of the image analysis and allow for a focused and efficient processing of the targeted image areas.
Claims 12 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Mun and Hayut as applied to claims 1 and 14 above, and further in view of Champlin (US Pub 20160350914, see IDS).
Re claim 12, the combined disclosure of Mun and Hayut as a whole discloses the image analysis method of claim 1, but fails however to explicitly disclose wherein the analysis data comprises vector data for each of pixels in the image of the analysis target cell.
This design is however disclosed by Champlin. Champlin discloses wherein the analysis data comprises vector data for each of pixels in the image of the analysis target cell (Par 10-12, 50, 62, 69, 124).
Therefore, it would have been obvious to one of ordinary skill in the art at the effective filing date of the invention to modify the disclosure of Mun in order to incorporate the image analysis of Champlin based on the rationale of the use of known techniques to improve similar designs in the same way, in this instance the specific processing shown allows for a more granular and specific consideration of the cell imaging shown in the base design and allows for a user to implement processing to search for design specific characteristics within the existing cellular analysis processing.
Re claim 18, the combined disclosure of Mun and Hayut as a whole discloses the image analysis apparatus of claim 14, but fails however to explicitly disclose wherein the analysis data comprises vector data for each of pixels in the image of the analysis target cell.
This design is however disclosed by Champlin. Champlin discloses wherein the analysis data comprises vector data for each of pixels in the image of the analysis target cell (Par 10-12, 50, 62, 69, 124).
Therefore, it would have been obvious to one of ordinary skill in the art at the effective filing date of the invention to modify the disclosure of Mun in order to incorporate the image analysis of Champlin based on the rationale of the use of known techniques to improve similar designs in the same way, in this instance the specific processing shown allows for a more granular and specific consideration of the cell imaging shown in the base design and allows for a user to implement processing to search for design specific characteristics within the existing cellular analysis processing.
Claims 11 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Mun and Hayut as applied to claims 1 and 14 above, and further in view of Correia De Matos Nolasco Lamas (herein after Cor) (US Pub 20170212028, see IDS).
Re claim 11, the combined disclosure of Mun and Hayut as a whole discloses the image analysis method of claim 1, but fails however to explicitly disclose wherein the analysis data comprises color data for each of pixels in the image of the analysis target cell.
This design is however disclosed by Cor. Cor discloses wherein the analysis data comprises color data for each of pixels in the image of the analysis target cell (Par 128, 172, 254, 298).
Therefore, it would have been obvious to one of ordinary skill in the art at the effective filing date of the invention to modify the disclosure of Mun in order to incorporate the image analysis of Cor based on the rationale of the use of known techniques to improve similar designs in the same way, in this instance it would be obvious to use the color considerations to more accurately differentiate between the components of the image and clearly determine the specific cell components and background areas under consideration to improve the diagnostic quality of the design while further helping to reduce analysis errors.
Re claim 17, the combined disclosure of Mun and Hayut as a whole discloses the image analysis method of claim 14, but fails however to explicitly disclose wherein the analysis data comprises color data for each of pixels in the image of the analysis target cell.
This design is however disclosed by Cor. Cor discloses wherein the analysis data comprises color data for each of pixels in the image of the analysis target cell (Par 128, 172, 254, 298).
Therefore, it would have been obvious to one of ordinary skill in the art at the effective filing date of the invention to modify the disclosure of Mun in order to incorporate the image analysis of Cor based on the rationale of the use of known techniques to improve similar designs in the same way, in this instance it would be obvious to use the color considerations to more accurately differentiate between the components of the image and clearly determine the specific cell components and background areas under consideration to improve the diagnostic quality of the design while further helping to reduce analysis errors.
Claims 9-10 are rejected under 35 U.S.C. 103 as being unpatentable over Mun and Hayut as applied to claim 1 above, and further in view of Xu (US Pub 20140206006, see IDS).
Re claim 9, the combined disclosure of Mun and Hayut as a whole discloses the image analysis method of claim 1, but fails however to explicitly disclose wherein the image of the analysis target cell contains a single analysis target cell.
This design is however disclosed by Xu. Xu discloses wherein the image of the analysis target cell contains a single analysis target cell (Par 13, 22, 115).
Therefore, it would have been obvious to one of ordinary skill in the art at the effective filing date of the invention to modify the disclosure of Mun in order to incorporate the specific image analysis design of Xu based on the rationale of the use of known techniques to improve similar designs in the same way, in this instance the specific processing shown allows for a more granular and specific consideration of the cell imaging shown in the base design and allows for a user to implement processing to search for design specific characteristics within the existing cellular analysis processing.
Re claim 10, the combined disclosure of Mun, Hayut and Xu as a whole discloses the image analysis method of claim 9, Xu further discloses wherein the image of the analysis target cell contains red blood cells along with the analysis target cell (Par 2, 6, 30, 38, 58-59).
Conclusion
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/MICHAEL R NEFF/ Primary Examiner, Art Unit 2631
