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 .
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1, 4-7, and 9-11 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Chan et al. (2019/0365341).
Regarding claim 1, Chan discloses a learner comprising:
at least one processor, wherein the processor is configured to:
reduce original noise of first learning data which is image data acquired by an imaging apparatus that includes the original noise generated in the imaging apparatus, using a noise reducer that is trainable (note images 153 in Fig. 1);
add simulated noise the first learning data in which the original noise is reduced to generate simulated-noise added first learning data, the simulated noise being generated, by a noise generator, to simulate the original noise generated in the imaging apparatus (note images 155 in Fig. 1; par. 81); and
train the noise reducer to minimize deviation between a distribution of the simulated-noise added first learning data and a distribution of second learning data that is the same data as the first learning data, and which includes the original noise of the first learning data, wherein the learner is configured to train the noise reducer (note 110 in Fig. 1; par. 45).
Regarding claim 4, Chan discloses the noise reducer is a deep learning model (note par. 45).
Regarding claim 5, Chan discloses target data for reducing noise via the noise reducer is image data (note 255).
Regarding claim 6, Chan discloses the image data is a radiation image (note PET images).
Regarding claim 7, Chan inherently discloses the processor is configured to train the noise reducer to make the distribution of the simulated-noise added first learning data and the distribution of the second learning data unidentifiable by a predetermined identifier. That is, noise segments added in Chan can only identified manually, but not by the processor (note par. 72 and 73).
Regarding claim 9, Chan discloses deviation is a Wasserstein distance or a value based on an information amount (note par. 74 and 95).
Regarding claims 10 and 11, see rejection to claim 1.
Allowable Subject Matter
Claims 12 and 13 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Response to Arguments
Applicant’s arguments with respect to the claim(s) have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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 MICHAEL LEE whose telephone number 571-272-7349. The examiner can normally be reached on Monday through Thursday from 9:00 am to 6:00 pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, John Miller, can be reached on 571-272-7353. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MICHAEL LEE/ Primary Examiner,
Art Unit 2422