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 .
This office action is in response to communication fled on 7/15/2026. Claims 1-16 are pending on this application.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-16 have been considered but are moot in view of the new grounds of rejection.
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.
Claim(s) 1, 3, 5-12, and 14-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fujimoto et al (US20200134287) in view of Anorga et al (US10891485) and Yamada (US20100104169).
Regarding claim 1, Fujimoto teaches an apparatus for determining material component concentrations in a sample (para. [0065]), comprising:
an imaging device (74 in fig. 1) for imaging a sample including material components to produce sample images (para. [0036], capture images of material components in the urine sample using the camera 74);
an acquisition unit configured to acquire material component images of respective material components from at least some of the sample images (para. [0008], extract a material component image identified as a material component, from plural images obtained by imaging a sample fluid containing plural types of material components and flowing through a flow cell);
a classification unit configured to classify the material component images into respective groups corresponding to a respective type of material component of the material components shown within a material component image (30 in fig. 4; para. [0058], The categorizing section 30 then categorizes the extracted material component images into predetermined categories (for example by the type, size, or shape of the material components, or by the presence or absence of a nucleus therein)), wherein a concentration of the material component in the sample is based on a cardinality of the material component images classified into a group of the groups corresponding to the material component (32 in fig. 4; para. [0008], derive a count per unit liquid volume of the material component contained in the sample fluid, for each predetermined category based on a number of material component images categorized by the categorizing section);
a calculation unit configured to calculate a concentration of at least one material component of the material components in the sample (para. [0008], derive a count per unit liquid volume of the material component contained in the sample fluid).
Fujimoto fails to teach an acceptance unit configured to determine whether a condition is satisfied indicating that reclassification of at least some of the material component images is recommended;
a control unit configured to, when the condition is satisfied, transmit the at least some of the material component images as classified are transmitted to a remote processing device through a network, the remote processing device configured to reclassify the at least some of the material component images and return reclassification information for the at least some of the material component images; and
a calculation unit configured to perform a calculation using the reclassification information.
However Anorga teaches an acceptance unit configured to determine whether a condition is satisfied indicating that reclassification of at least some of an image is recommended (210 in fig. 2; col. 15 lines 4-24, In some implementations, server classification may be selectively utilized, e.g., when local classification results do not include a category for an image, or when local classification results include multiple categories, e.g., with confidence scores that do not meet a confidence score threshold);
a control unit configured to, when the condition is satisfied, transmit the at least some of the image as classified are transmitted to a remote processing device through a network (col. 15 lines 41-49, A further technical advantage is that only such image representations are sent to the server for which the local classification results are not sufficient, e.g., to display one or more suggested actions, or to perform an action based on the image), the remote processing device configured to reclassify the at least some of the material component images and return reclassification information for the at least some of the material component images (col. 16 lines 58-66, local classification results may be sent to the server. In some implementations, transmitting the image representation to the server also includes sending information to the server that indicates that the image is to be processed by the server only to generate classification results; col. 17 lines 3-12 and lines 38-42); and
a calculation unit configured to perform a calculation using the reclassification information (col. 18 lines 55-60, In block 226, image categories and/or suggested actions are determined based on one or more of local classification results and server classification results).
Therefore taking the combined teachings of Fujimoto and Anorga as a whole, it would have been obvious to one of ordinary skill in the art at the time the invention was filed to incorporate the features of Anorga into the apparatus of Fujimoto. The motivation to combine Anorga and Fujimoto would be to save processing costs (col. 15 lines 41-44 of Anorga).
Fujimoto also fails to teach wherein the calculation unit is initially configured to calculate a concentration of the material components in the sample using the groups and recalculate the concentration of at least one material component of the material components in the sample using the reclassification information.
However Yamada teaches calculating a concentration of material components in a sample using groups (para. [0099]; para. [0171]) and recalculate the concentration of at least one material component of the material components in the sample using reclassification information (para. [0191]; para. [0193], the CPU 751a stores a recount result with the changed classification in the RAM 751c; para. [0196], the CPU 751a transmits the recount result, including the value counted for each blood cell type, which reflects the changed classification result to the image processing unit 73).
Therefore taking the combined teachings of modified Fujimoto and Yamada as a whole, it would have been obvious to one of ordinary skill in the art at the time the invention was filed to incorporate the features of Yamada into the apparatus of modified Fujimoto. The motivation to combine Yamada and modified Fujimoto would be to correctly count at least the specimens of a healthy person, so that the accuracy in variation can be improved by mainly using the count result of the specimens of the healthy person (para. [0209] of Yamada).
Regarding claim 3, the modified apparatus of Fujimoto teaches an apparatus wherein the sample is urine (para. [0036] of Fujimoto).
Regarding claim 5, the modified apparatus of Fujimoto teaches an apparatus wherein the control unit is configured transmit the at least some of the material component images only when the condition is satisfied (col. 15 lines 41-49 of Anorga) and data transmission to the remote processing device is permitted in advance (it would be obvious to allow data transmission in advance to save processing time).
Regarding claim 6, the modified apparatus of Fujimoto teaches an apparatus wherein the control unit is configured to transmit a respective classification result of the at least some of the material component images to the remote processing device through the network together with the at least some of the material component images (col. 16 lines 58-66 of Anorga, For example, one or more of an image thumbnail, a knowledge representation, and local classification results may be sent to the server).
Regarding claim 7, the modified apparatus of Fujimoto teaches an apparatus wherein the calculation unit is configured to calculate a concentration of respective ones of the material components in the sample using the groups (32 in fig. 4 and para. [0008] of Fujimoto, derive a count per unit liquid volume of the material component contained in the sample fluid, for each predetermined category based on a number of material component images categorized by the categorizing section).
Regarding claim 8, the modified apparatus of Fujimoto teaches an apparatus wherein an updated model for the classification unit is trained using results from the classification unit and the reclassification information (col. 13 lines 56-63 of Anorga).
Regarding claim 9, the modified system of Fujimoto teaches a system for determining material component concentrations in a sample, comprising:
the apparatus of claim 1 as a first processing device (see the rejection of claim 1 above); and
the remote processing device as a second processing device (104 in fig. 1 of Anorga) connected to the first processing device (120 in fig. 1 of Anorga) through the network (130 in fig. 1 of Anorga), wherein the second processing device includes:
a reclassification unit configured to reclassify a material component image among the at least some of the material component images received from the first processing device into a group corresponding to a type of a material component different from that determined by the classification unit (226 in fig. 2 and col. 18 lines 55-64 of Anorga); and
a return unit configured to return a reclassification result of the material component image reclassified by the reclassification unit to the first processing device (224 in fig. 2 of Anorga).
Regarding claim 10, the modified system of Fujimoto teaches a system wherein:
the reclassification unit comprises a trained machine-learning model (col. 4 lines 60-64 and col. 16 lines 2-6 of Anorga).
Regarding claim 11, the claim recites similar subject matter as claim 1 and is rejected for the same reasons as stated above.
Regarding claim 12, the modified method of Fujimoto teaches a method wherein the reclassification information includes at least one material component different from the respective types of material components available for the classifying into the groups (col. 18 lines 55 – col. 19 line 6 of Anorga).
Regarding claim 14, the modified method of Fujimoto teaches a method wherein executing the control results in transmitting all of the material component images as classified (para. [0008] of Fujimoto) through the network (130 in fig. 1 of Anorga) to the remote processing device (104 in fig. 4 and col. 15 lines 41-49 of Anorga).
Regarding claim 15, the modified method of Fujimoto teaches a method comprising:
initially calculating a respective concentration of the material components in the sample using the groups (32 in fig. 4 and para. [0008] of Fujimoto).
Regarding claim 16, the claim recites similar subject matter as claim 1 and is rejected for the same reasons as stated above.
Claim(s) 2, 4, and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fujimoto et al (US20200134287), Anorga et al (US10891485) and Yamada (US20100104169) in view of Busenhart et al (US9443058).
Regarding claim 2, the modified apparatus of Fujimoto fails to teach an apparatus wherein the control unit is configured to transmit the at least some of the material component images when at least one of a qualitative test result of the sample obtained by a qualitative analysis device configured to execute qualitative measurement of the sample satisfies the condition or error information in which an abnormality occurring in the qualitative analysis device is recorded satisfies the condition.
However Busenhart teaches images when at least one of a qualitative test result of the sample obtained by a qualitative analysis device configured to execute qualitative measurement of the sample satisfies the condition (col. 3 lines 18-26, col. 5 lines 27-35) or error information in which an abnormality occurring in the qualitative analysis device is recorded satisfies the condition (col. 5 lines 42-64). It would be obvious to transmit the at least some of the material component images, as taught in claim 1 by Anorga, in response to the results of Busenhart.
Therefore taking the modified teachings of modified Fujimoto with Busenhart as a whole, it would have been obvious to one of ordinary skill in the art at the time the invention was filed to incorporate the features of Busenhart into the apparatus of modified Fujimoto. The motivation to combine Busenhart and modified Fujimoto would be to obtain higher quality and more reliable results (col. 5 lines 24-26 of Busenhart).
Regarding claim 4, the modified apparatus of Fujimoto fails to teach an apparatus wherein the condition is represented by at least one of a magnitude relationship between a concentration of a material component of a type designated by a user and a threshold designated by a user, a magnitude relationship between a value of a qualitative item designated by a user among qualitative items in a qualitative test result of the sample and a threshold in the qualitative item, or an occurrence status of an error item designated by a user among error items in error information.
However Busenhart teaches wherein a condition is represented by at least one of a magnitude relationship between a concentration of a material component of a type designated by a user and a threshold designated by a user (claim 18 and col. 5 lines 27-35, it would be obvious for a user to set a desired threshold) or an occurrence status of an error item designated by a user among error items in error information (col. 5 lines 42-52, it would be obvious for a user to set a desired threshold).
Therefore taking the modified teachings of modified Fujimoto with Busenhart as a whole, it would have been obvious to one of ordinary skill in the art at the time the invention was filed to incorporate the features of Busenhart into the apparatus of modified Fujimoto. The motivation to combine Busenhart and modified Fujimoto would be to obtain higher quality and more reliable results (col. 5 lines 24-26 of Busenhart).
Regarding claim 13, the claim recites similar subject matter as claim 4 and is rejected for the same reasons as stated above.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LEON VIET Q NGUYEN whose telephone number is (571)270-1185. The examiner can normally be reached Mon-Fri 11AM-7PM.
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/LEON VIET Q NGUYEN/Primary Examiner, Art Unit 2663
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