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 Interpretation
Claim 1 contains limitations requiring particular construction.
The term “data driven model” has no specific definition in the written description, and the plain language of the term is any model that is constructed based on any data input. This is obviously broader than is intended, as the “mathematical model” is also constructed based on the sensor data, and the “data driven model” is described as making certain corrections to the “mathematical model.” (See Applicant’s Written Description, pp. 20-21.) The phrase is not written to invoke 35 U.S.C. 112(f), and therefore cannot be drawn specifically to the described formulae. Therefore the term “data driven model” is construed herein as a corrective or additional term beyond an ordinary regression model.
Claim Rejections - 35 USC § 103
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 1-27 are rejected under 35 U.S.C. 103 as being unpatentable over Besson et al. (2015/0223766) in view of Zhou et al. (2019/0313993).
Regarding claim 1, Besson teaches a method for correcting the nonlinearity associated with photon counting detectors (PCDs) of imaging devices (Besson, [0066]), the method comprising: providing a first scanning device and a second scanning device, wherein each of the first and second scanning devices comprises an X-ray source configured to emit an X-ray beam and a detector array in alignment with the X-ray beam, wherein the detector array of the first scanning device comprises a plurality of energy integrating detectors (EID) and the detector array of the second scanning device comprises a plurality of photo counting detectors (PCD) (Besson, Fig. 8) ; detecting an X-ray beam passed through an object to be scanned with the plurality of energy integrating detectors (EID); detecting an X-ray beam passed through the object to be scanned with the plurality of photo counting detectors (PCD); recording the X-ray beam detected by the plurality of energy integrating detectors (EID) as a first data set; recording the X-ray beam detected by the plurality of photo counting detectors (PCD) as a second data set (Besson, Fig. 9, items 904, 906, 908); and generating a scan image of the object from the second data set.
Besson lacks explicit teaching of creating a mathematical model using the first data set and the second data set; creating a data driven model to supplement the mathematical model, wherein the data driven model addresses limitations of the mathematical model and extends the correction range; applying the mathematical model and the data driven model to the second data set so as to derive an attenuation factor; applying the attenuation factor to the second data set.
Zhou teaches creating a mathematical model using the first data set and the second data set (Zhou, [0030], first mathematical model estimated from calibration scans, Besson indicates generating calibration scan from energy integrating detectors); creating a data driven model to supplement the mathematical model, wherein the data driven model addresses limitations of the mathematical model and extends the correction range (Zhou, [0034]; additional correction factors applied to model); applying the mathematical model and the data driven model to the second data set so as to derive an attenuation factor; applying the attenuation factor to the second data set (Zhou, image generation step 130).
It would have been obvious to one of ordinary skill in the art to use the detailed correction models of Zhou to enhance and implement the directive of Besson to use the energy integrating detector readings to correct the photon counting detector readings.
Regarding claim 2, the combination of Besson and Zhou further teaches the attenuation factor applied to the second data set corrects for the pulse pileup effect. (Zhou, [0031])
Regarding claim 3, the combination of Besson and Zhou further teaches the attenuation factor applied to the second data set corrects for the charge sharing effect. (Zhou, [0028] indicating charge sharing as known problem, [0034] describing application of corrections to known projection errors)
Regarding claim 4, the combination of Besson and Zhou further teaches the first scanning device and the second scanning device comprise computerized tomography (CT) imaging machines. (Besson, [0026], [0027] CT system described)
Regarding claim 5, the combination of Besson and Zhou further teaches the X-ray sources of the first scanning device and the second scanning device comprise X-ray tubes. (Besson, [0029] X-ray source(s) 118)
Regarding claim 6, the combination of Besson and Zhou further teaches the X-ray beam emitted by the X-ray tubes is a polychromatic X-ray beam. (Besson, [0066], existence of wavelength discrimination and lower/higher energy bins implies the generation of polychromatic X-rays)
Regarding claim 7, the combination of Besson and Zhou further teaches the data driven model is created by extracting data from the second data set prior to deriving the attenuation factor. (Zhou, [0042] – [0058], many of the described corrections use data directly from the detector)
Regarding claim 8, the combination of Besson and Zhou further teaches the computerized tomography (CT) imaging machines comprise identically configured computerized tomography (CT) imaging machines. (Besson, [0026], [0027], same machine, two detectors)
Regarding claim 9, claim 9 is rejected on the same grounds as claim 1, as it has the same substantive limitations.
Regarding claim 10, claim 10 is rejected on the same grounds as claim 1, as it has the same substantive limitations.
Claims 11-18 are rejected on the same grounds as claims 2-8, as they have the same substantive limitations.
Claim 19 is rejected on the same grounds as claim 1, as it has the same substantive limitations.
Claims 20-27 are rejected on the same grounds as claims 2-8, as they have the same substantive limitations.
Conclusion
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/EDWIN C GUNBERG/ Primary Examiner, Art Unit 2884