Detailed Action
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
2. Receipt is acknowledged of certified copies of papers submitted under 35 U.S.C. 119(a)-(d), which papers have been placed of record in the file.
Claim Analysis - 35 USC § 112
3. The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
4. This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are: “output device” in claim 1.
Because the claim limitation is being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, claim 1 is interpreted to cover the corresponding structure described in the specification that achieves the claimed function, and equivalents thereof.
As for the limitation "output device”, a review of the specification shows that the following appears to be the corresponding structure described in the specification for the 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph): [0027] of the specification and Fig. 1 of the drawing disclose " output device” correspond to a display monitor.
If applicant wishes to provide further explanation or dispute the examiner's interpretation of the corresponding structure, applicant must identify the corresponding structure with reference to the specification by page and line number, and to the drawing, if any, by reference characters in response to this Office action.
If applicant does not wish to have the claim limitation treated under 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph), applicant may amend the claim so that it will clearly not invoke 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph), or present a sufficient showing that the claim recites sufficient structure, material, or acts for performing the claimed function to preclude application of 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph).
Claim Rejections - 35 USC § 112
5. The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION. — The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
6. Claims 19-20 are rejected under 35 U.S.C. 112(b) (pre-AIA 35 U.S.C. 112, second paragraph), as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Claim 19 recites the limitation “The computer-readable storage medium of claim 17” and claim 20 recites the limitation “The computer-readable storage medium of claim 19”. There is insufficient antecedent basis for the limitation “The computer-readable storage medium” in the claims. For the purpose of the examination, claims 19 and 20 are interpreted as being dependent upon claim 18.
Claim Rejections - 35 USC § 102
7. 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.
8. Claims 1-2, 4-5, and 14-15 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by JEREBKO (US 20180061090 A1).
Regarding claim 1, JEREBKO (Figs. 1-8) discloses a computing system (Fig. 8; computing unit 11; [0018]-[0019] and [0079]-[0081]), comprising: a memory with instructions including a digitally reconstructed radiograph view optimization instruction (storage and instructions; [0018]-[0019]); a processor (computing unit 11 comprising a microprocessor; [0019]) configured to execute the digitally reconstructed radiograph view optimization instruction to generate a plurality of digitally reconstructed radiographs based on a plurality of different sets of projection parameters and three-dimensional computed tomography image data (Figs. 1-7, e.g., Fig. 1, step I, step II.5, and step III, and [0059]-[0060], [0065]-[0067]; reconstructed radiographs based on projection parameters PP and 3D CT image data VB) and to identify an optimal sub-set of the plurality of digitally reconstructed radiographs to be read for a same reason that the three- dimensional computed tomography image data was acquired (e.g., Figs. 4-7 and [0005], [0045], [0067], [0072], [0076]; desired or optimal reconstructed radiographs); and an output device configured to display the identified optimal sub-set of the plurality of digitally reconstructed radiographs for reading (Figs. 1 and 8 and [0079]; display device 15 outputs images).
Regarding claim 2, JEREBKO (Figs. 1-8) discloses the system of claim 1, wherein the processor is further configured to determine the different sets of projection parameters based on a pre-defined list of projection parameters (Fig. 1, steps II.6 and II.7; [0065]-[0067] and [0031]; e.g., user-defined projection parameters).
Regarding claim 4, JEREBKO (Figs. 1-8) discloses the system of claim 1, wherein the different sets of projection parameters include projection parameters for generating a digitally reconstructed radiograph in an arbitrary direction ([0031]-[0032]).
Regarding claim 5, JEREBKO (Figs. 1-8) discloses the system of claim 1, wherein the processor employs artificial intelligence to identify the optimal sub-set of the plurality of digitally reconstructed radiographs ([0067] and claim 14; machine learning).
Regarding claim 14, JEREBKO (Figs. 1-8) discloses the system of claim 1, wherein the processor is further configured to identify an optimal view direction of the sub-set directly from the three-dimensional computed tomography image data (Figs. 4-7 and [0033]-[0034], [0038], and [0045], [0072]; optimal projection direction).
Regarding claim 15, JEREBKO (Figs. 1-8) discloses a computer-implemented method, comprising: generating a plurality of digitally reconstructed radiographs based on a plurality of different sets of projection parameters and three-dimensional computed tomography image data (Figs. 1-7, e.g., Fig. 1, step I, step II.5, and step III, and [0059]-[0060], [0065]-[0067]; reconstructed radiographs based on projection parameters PP and 3D CT image data VB); identifying an optimal sub-set of the plurality of digitally reconstructed radiographs to be read for a same reason that the three-dimensional computed tomography image data was acquired (e.g., Figs. 4-7 and [0005], [0045], [0067], [0072], [0076]; desired or optimal reconstructed radiographs); and displaying the identified optimal sub-set of the plurality of digitally reconstructed radiographs for reading (Figs. 1 and 8 and [0079]; display device 15 outputs images).
Claim Rejections - 35 USC § 103
9. 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.
10. Claims 6-13 and 17 are rejected under 35 U.S.C. 103 as unpatentable over JEREBKO (US 20180061090 A1) in view of GEORGESCU (US 20150238148 A1).
Regarding claim 6, JEREBKO (Figs. 1-8) discloses the system of claim 5, but does not disclose wherein the artificial intelligence includes a Deep Learning network. However, GEORGESCU (e.g., Fig. 5B) discloses a computing system, wherein the processor employs artificial intelligence to identify the optimal sub-set of the plurality of digitally reconstructed radiographs, and wherein the artificial intelligence includes a Deep Learning network (e.g., Figs. 1-5 and 13; using deep neural networks in medical image data). Therefore, it would have been obvious to one skilled in the art at the effective filing date of the claimed invention to incorporate the teaching from GEORGESCU to the computing system and method of JEREBKO. The combination/motivation would be to provide a computing system and a method for an anatomical object detection in medical image data using deep neural networks.
Regarding claim 7, JEREBKO (Figs. 1-8) discloses the system of claim 5, but does not disclose wherein the identification is based on a classification algorithm. However, GEORGESCU (e.g., Fig. 5B) discloses wherein the identification is based on a classification algorithm ([0021]-[0022], [0056], and [0058]-[0061]; classification algorithm). Therefore, it would have been obvious to one skilled in the art at the effective filing date of the claimed invention to incorporate the teaching from GEORGESCU to the computing system and method of JEREBKO. The combination/motivation would be to provide a computing system and a method for an anatomical object detection in medical image data using machine learning.
Regarding claim 8, JEREBKO (Figs. 1-8) discloses the system of claim 5, but does not disclose wherein the identification is based on a regression algorithm. However, GEORGESCU (e.g., Fig. 5B) discloses wherein the identification is based on a regression algorithm ([0023], [0032]-[0035], [0038], [0053]-[0054], and [0067]; regression algorithm). Therefore, it would have been obvious to one skilled in the art at the effective filing date of the claimed invention to incorporate the teaching from GEORGESCU to the computing system and method of JEREBKO. The combination/motivation would be to provide a computing system and a method for an anatomical object detection in medical image data using machine learning.
Regarding claim 9, JEREBKO (Figs. 1-8) discloses the system of claim 5, but does not disclose wherein the identification is based on a detection algorithm. However, GEORGESCU (e.g., Fig. 5B) discloses wherein the identification is based on a detection algorithm (Figs. 1, 5, and 13, and [0021]-[0025], [0028], [0037]-[0038], [0044]-[0045], and [0070]; detection of an object of interest using deep learning model). Therefore, it would have been obvious to one skilled in the art at the effective filing date of the claimed invention to incorporate the teaching from GEORGESCU to the computing system and method of JEREBKO. The combination/motivation would be to provide a computing system and a method for an anatomical object detection in medical image data using machine learning.
Regarding claim 10, JEREBKO in view of GEORGESCU discloses the system of claim 5, GEORGESCU (e.g., Fig. 5B) discloses wherein the processor is further configured to generate and display a heat map based on a result of the detection algorithm, wherein the heat map highlights a region of interest in the optimal sub-set of the plurality of digitally reconstructed radiographs (Figs. 11-12 and 14; [0038], [0041], and [0044], detection of an object of interest, [0051], detected anatomical object can be displayed on a display device). Therefore, it would have been obvious to one skilled in the art at the effective filing date of the claimed invention to incorporate the teaching from GEORGESCU to the computing system and method of JEREBKO for the same reason above.
Regarding claim 11, JEREBKO in view of GEORGESCU discloses the system of claim 9, GEORGESCU (e.g., Fig. 5B) discloses wherein the processor is further configured to apply a detection algorithm to at least a sub-portion of the three-dimensional computed tomography image data and evaluate the digitally reconstructed radiographs based on a visibility of structures detected in the digitally reconstructed radiographs (Figs. 5, 7-8, and 14; [0051], [0057], [0064], and [0073]). Therefore, it would have been obvious to one skilled in the art at the effective filing date of the claimed invention to incorporate the teaching from GEORGESCU to the computing system and method of JEREBKO for the same reason above.
Regarding claim 12, JEREBKO in view of GEORGESCU discloses the system of claim 11, GEORGESCU (e.g., Fig. 5B) discloses wherein the processor evaluates the digitally reconstructed radiographs based on a size of the detected structures in the digitally reconstructed radiographs (e.g., Fig. 14; [0073] and [0055]-[0056]). Therefore, it would have been obvious to one skilled in the art at the effective filing date of the claimed invention to incorporate the teaching from GEORGESCU to the computing system and method of JEREBKO for the same reason above.
Regarding claim 13, JEREBKO in view of GEORGESCU discloses the system of claim 11, GEORGESCU (e.g., Fig. 5B) discloses wherein the processor is further configured to generate and display a heat map based a result of the detection algorithm and a result of the segmentation, wherein the heat map highlights a region of interest in the optimal sub-set of the plurality of digitally reconstructed radiographs (Figs. 11-12 and 14; [0038], [0041], and [0044], detection of an object of interest, [0051], detected anatomical object can be displayed on a display device). Therefore, it would have been obvious to one skilled in the art at the effective filing date of the claimed invention to incorporate the teaching from GEORGESCU to the computing system and method of JEREBKO for the same reason above.
Regarding claim 17, JEREBKO (Figs. 1-8) discloses the computer-implemented method of claim 15, but does not disclose the method further comprising: identifying the optimal sub-set of the plurality of digitally reconstructed radiographs determining based on a trained convolutional neural network. However, GEORGESCU (e.g., Fig. 5B) discloses the method further comprising: identifying the optimal sub-set of the plurality of digitally reconstructed radiographs determining based on a trained convolutional neural network ([0031] and claim 15; CNN). Therefore, it would have been obvious to one skilled in the art at the effective filing date of the claimed invention to incorporate the teaching from GEORGESCU to the computing system and method of JEREBKO. The combination/motivation would be to provide a computing system and a method for an anatomical object detection in medical image data using deep neural networks.
11. Claims 3 and 16 are rejected under 35 U.S.C. 103 as unpatentable over JEREBKO (US 20180061090 A1) in view of NOORDHOEK (US 20110135053 A1).
Regarding claim 3, JEREBKO (Figs. 1-8) discloses the system of claim 1, wherein the different sets of projection parameters include projection parameters for generating a digitally reconstructed radiograph along a curved trajectory ([0004]; cone-beam projection indicates a circular trajectory). As another reference, NOORDHOEK (Figs. 1-5) discloses a computing system, wherein the different sets of projection parameters include projection parameters for generating a digitally reconstructed radiograph along a curved trajectory (Figs. 3-4; circular trajectory). Therefore, it would have been obvious to one skilled in the art at the effective filing date of the claimed invention to incorporate the teaching from NOORDHOEK to the computing system and method of JEREBKO. The combination/motivation would be to provide a 3D rotational X-ray imaging system for an anatomical object detection.
Regarding claim 16, JEREBKO (Figs. 1-8) discloses the computer-implemented method of claim 15, but does not disclose determining the different sets of projection parameters using regression to infer projection directions from the three-dimensional computed tomography image data. However, NOORDHOEK (Figs. 1-5) discloses a computer-implemented method, comprising: determining the different sets of projection parameters using regression to infer projection directions from the three-dimensional computed tomography image data (e.g., Fig. 4; [0029]-[0030] and [0042]-[0044]; projections using regression algorithm). Therefore, it would have been obvious to one skilled in the art at the effective filing date of the claimed invention to incorporate the teaching from NOORDHOEK to the computing system and method of JEREBKO. The combination/motivation would be to provide a 3D rotational X-ray imaging system for an anatomical object detection.
12. Claim 18 is rejected under 35 U.S.C. 103 as unpatentable over JEREBKO (US 20180061090 A1) in view of KEMP (US 20190328461 A1).
Regarding claim 18, JEREBKO (Figs. 1-8) discloses a computer-readable storage medium storing computer executable instructions (storage and instructions; [0018]-[0019]), which when executed by a processor (computing unit 11 comprising a microprocessor; [0019]) of a computer cause the processor to: generate a plurality of digitally reconstructed radiographs based on a plurality of different sets of projection parameters and three-dimensional computed tomography image data (Figs. 1-7, e.g., Fig. 1, step I, step II.5, and step III, and [0059]-[0060], [0065]-[0067]; reconstructed radiographs based on projection parameters PP and 3D CT image data VB); identify an optimal sub-set of the plurality of digitally reconstructed radiographs to be read for a same reason that the three-dimensional computed tomography image data was acquired (e.g., Figs. 4-7 and [0005], [0045], [0067], [0072], [0076]; desired or optimal reconstructed radiographs); and display the identified optimal sub-set of the plurality of digitally reconstructed radiographs for reading (Figs. 1 and 8 and [0079]; display device 15 outputs images).
JEREBKO does not disclose for detecting and labelling vertebrae of a spine in volumetric image data. However, KEMP (Figs. 1-9) discloses a computer-readable storage medium storing computer executable instructions, for detecting and labelling vertebrae of a spine in volumetric image data (Figs5-6 and [0074], [0081], and [0096]; labelling vertebrae of a spine), which when executed by a processor. Therefore, it would have been obvious to one skilled in the art at the effective filing date of the claimed invention to incorporate the teaching from KEMP to the computing system and method of JEREBKO. The combination/motivation would be to provide a medical system used for an anatomical object detection and used to assist in a procedure.
13. Claims 19-20 are rejected under 35 U.S.C. 103 as unpatentable over JEREBKO (US 20180061090 A1) in view of KEMP (US 20190328461 A1) and further in view of NOORDHOEK (US 20110135053 A1).
Regarding claim 19, JEREBKO in view of KEMP discloses the computer-readable storage medium of claim 17, but does not disclose wherein the computer executable instructions further cause the processor to: determine the different sets of projection parameters using regression to infer projection directions from the three-dimensional computed tomography image data. However, NOORDHOEK (Figs. 1-5) discloses wherein the computer executable instructions further cause the processor to: determine the different sets of projection parameters using regression to infer projection directions from the three-dimensional computed tomography image data (e.g., Fig. 4; [0029]-[0030] and [0042]-[0044]; projections using regression algorithm). Therefore, it would have been obvious to one skilled in the art at the effective filing date of the claimed invention to incorporate the teaching from NOORDHOEK to the computing system and method of JEREBKO in view of KEMP. The combination/motivation would be to provide a 3D rotational X-ray imaging system for an anatomical object detection.
Regarding claim 20, JEREBKO in view of KEMP and further in view of NOORDHOEK discloses the computer-readable storage medium claim 17, KEMP discloses wherein the computer executable instructions further cause the processor to: identify the optimal sub-set of the plurality of digitally reconstructed radiographs determining based on a trained convolutional neural network (Figs. 4-6; CNN; [0017]-[0019]). Therefore, it would have been obvious to one skilled in the art at the effective filing date of the claimed invention to incorporate the teaching from KEMP to the computing system and method of JEREBKO. The combination/motivation would be to provide a computing system and a method for an anatomical object detection in medical image data using deep neural networks.
Inquiry
Any inquiry concerning this communication or earlier communications from the examiner should be directed to YUZHEN SHEN whose telephone number is (571)272-1407. The examiner can normally be reached on 9:00-18:00.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Chanh Nguyen can be reached on 571-272-7772. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/YUZHEN SHEN/Primary Examiner, Art Unit 2623