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 .
DETAILED ACTION
Claims 1–15 have been submitted for examination.
Claims 1–2, 6, 9, 10, and 13 have been examined and rejected.
Claims 3–5, 7–8, 11–12, and 14–15 are objected to.
Allowable Subject Matter
Claims 3–5, 7–8, 11–12, and 14–15 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.
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 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 of this title, 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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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 1–2, 6, 9, 10, and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. (US 2021/0112187) in view of Knoll et al. (US 10,671,939).
Regarding claim 1, Chen discloses:
A computer implemented method for calibrating system parameters (Chen, ¶ [0039], “step two, the position of the LED array (1) is calibrated, using the resolution board as the specimen (4) to be examined,”) associated with an image reconstruction system; the method comprising:
obtaining captured images by illuminating a sample with one or more light sources associated with an imaging device of the image reconstruction system; (Chen, ¶[0040], “step three, raw images are captured, using the LED array (1) as an illumination source of a high illumination-numerical-aperture based large field-of-view high-resolution microscopic imaging device, sequentially lighting up each LED unit (8) of the LED array (1), after illuminating the specimen (4) to be examined, the corresponding low-resolution raw images are collected;”) characterized by iteratively performing:
obtaining a high resolution representation of the captured images, wherein the high resolution representation is generated by the image reconstruction system based on the system parameters and the captured images; (Chen, ¶ [0042], “step five, high-resolution images are initialized, adding and averaging all the low-resolution bright-field images among the brightness-corrected low-resolution images, and then initializing the amplitude and phase of the high-resolution images by up-sampling;”)
generating an approximate function based on the high resolution representation and the captured images, wherein the approximate function is a function of the system parameters; and (Chen, ¶ [0043], “step six, iterative reconstruction; each of the brightness corrected low-resolution images is subjected to synthetic aperture calculation one by one in the frequency domain by using pixel binning based Fourier ptychographic recovery method and the updating coefficient is gradually reduced; the cost function value is used as a criterion, and when the cost function value is less than a given threshold, the iteration is stopped. and at this moment, the amplitude and phase of the high-resolution images are the final reconstructed large field-of-view high-resolution microscopic images;”)
Chen does not explicitly teach “generating an updated set of system parameters by optimizing the approximate function.”.
In a similar field of endeavor Knoll teaches:
generating an updated set of system parameters by optimizing the approximate function. (Knoll, col. 4, ln. 45–65, “By reformulating image reconstruction as an optimized variational network, the exemplary system, method and computer-accessible medium, according to an exemplary embodiment of the present disclosure, can learn a complete reconstruction procedure, including filter kernels, and penalty functions to separate between true image content and artifacts, all parameters that normally have to be tuned manually, as well as the associated numerical procedure.”)
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine the system for obtaining a high resolution representation as taught by Chen with the system for automatic tuning of parameters as taught by Knoll, the motivation is to “decouple[] from the time critical image reconstruction procedure, which can then be performed in near real time without interruption of clinical workflow.” as taught by Knoll (col. 4, ln. 64–67).
Regarding claims 2, 6, 10, and 13, the combination of Chen and Knoll teaches:
The method according to claim 1, wherein the system parameters comprise one or more of optical data, geometrical data, alignment data, illumination plane to sample separation data, magnification data, wavelength data, and thresholding data. (Chen, ¶ [0039], “step two, the position of the LED array (1) is calibrated, using the resolution board as the specimen (4) to be examined,”)
Regarding claim 9 the combination of Chen and Knoll teaches:
The imaging device according to claim 6, further comprising: one or more controllable light sources placed at a discrete position; a tube lens; one or more objective lens; and an imaging capturing unit. (Chen, ¶ [0021], “Light emitted by the i-th lit LED unit (8) of the LED array (1) passes through the condenser (3) and converges to become parallel light illuminating a specimen (4) to be examined, which is placed on the stage (2); part of the diffracted light passing through the specimen (4) is collected by the microscopic objective (5), converged by the tube lens (6), and reaches the imaging plane of the camera (7), forming an intensity image recorded by the camera (7). Each LED unit in LED array (1) can be individually lighted up, and the specific method of lighting up LED units is a prior art, and the implementation circuit can be achieved by adopting (but is not limited to) a prior art such as microcontrollers, an ARM, or a programmable logic device and the like;”)
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL B PIERORAZIO whose telephone number is (571)270-3679. The examiner can normally be reached on Monday - Thursday, 8am - 5pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Nasser Goodarzi can be reached on 5712704195. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MICHAEL B. PIERORAZIO/Primary Examiner, Art Unit 2426