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 .
Notice to Applicants
This communication is in response to the action filed on 08/12/2024.
Claims 1-20 are pending.
Information Disclosure Statement
The information disclosure statement (IDS) filed on 08/12/2024 has been considered.
Claim Rejections - 35 USC § 102
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 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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-2, 5-12, 14-15, 18-20 are rejected under 35 § U.S.C. 102(a)(1) as being anticipated by US 12,588,883 B2 to LAZAREV et al. (hereinafter “LAZAREV”).
As per claim 1, LAZAREV discloses a method for post-processing radiographs from radiographic data including spectral recordings of a region of interest of an object (a computing system and method for post/preprocessing of radiographic x ray images and determine a region of interest of the radiographic images of a subject; abstract; figs 1, 9-10; column 21, lines 5-67; column 29, line 60-column 30, line 15), the method comprising: creating, from the radiographs, a first image in which a first material of the object is highlighted and a second material of the object is suppressed (generating from the radiographic x-ray images a first image wherein cancer tissues is given a different diffraction pattern (highlighted) in order to differentiate the cancerous tissues that was identified from the other tissues and a second image wherein the breast tissues of the scan are more transparent and see through to further highlight the potentially cancerous tissues and is done by using transparent channels 90 of spectral energy from the radiograph/x-ray device and causes materials such as the filter, the compression plate, and bones are more opaque and transparent; abstract; figs 1, 2B, 9-10; column 17, lines 4-51; column 18, lines 20-39; column 21, lines 5-67), the first material having different spectral attenuation properties than the second material (the healthy breast tissue appearing more opaque and transparent than the cancerous tissues due to its different spectral properties when the x ray radiation and its beams are applied using the device; abstract; figs 1, 2B, 9-10; column 17, lines 4-51; column 18, lines 20-39; column 29, line 60-column 30, line 12); creating, from the radiographs, a second image in which the second material is highlighted and the first material is suppressed (using the radiographs the system is adapted to use/generate images of diffraction patterns which are the interactions of a radiation x-ray beam with a tissue and depending on the tissue type and its spectral properties appear differently in the image allowing the user to diagnose the tissue types and would allow for the healthy breast tissue to be highlighted and the cancerous tissue to be suppressed/made opaque/translucent based on adjustment of algorithm parameters and weights which control the radiography/x-ray device; abstract; figs 6A-6B; column 29, line 60-column 30, line 60; column 39, lines 1-50; column 40, lines 3-10); post-processing the first image and the second image, wherein the first image is post-processed by a first filter module and the second image is post-processed by a second filter module (the computing system applies post processing to the images by using filters, for example the collimated x-ray device uses a first filter made of molybdenum, rhodium, aluminum, copper, and/or tin filters and two dimensional detector, is used to generate the first image such that the breast tissue is opaque/transparent and cancerous tissue is highlighted, and further plate 12 is said to be transparent, the system to alter the image for image two would switch filter types to a filter with spectral/radiographic properties that would cause the healthy tissue of the breast to be highlighted and the cancerous tissues to be opaque or more transparent based on the radiation beams applied; NOTE; different radiograph filters of different materials can change how various tissues appear in an image by altering the energy spectrum of the X-ray beam before it reaches the patient and switching between two filter types would result in different tissues being highlighted in the respective images; abstract; figs 1, 2B, 9-10; column 16, lines 20-50; column 17, lines 4-51; column 18, lines 20-39; column 21, lines 5-67); combining the post-processed first image and the post-processed second image to form a single image in which the first material and the second material are depicted (using machine learning algorithms that are trained to detect presence of cancer use the x-ray, and radiograph images 6A as inputs in order to generate image 6B to determine known diseases in the tissue; fig 11; column 22, lines 15-35; column 39, lines 1-30); and outputting the single image (the system is adapted to output figure 6b and a diagnosis indicator to the user; figs 6B and 11; column 6, lines 1-51; column 22, lines 15-35; column 39, line 50-column 40, line 10).
As per claim 2, LAZAREV discloses the method as claimed in claim 1, wherein the first material is at least one of bones or a contrast agent (method of controlling an X-ray system comprises: measuring the denseness of the breast tissue using an absorption contrast imaging apparatus and a contrast plate/filter and contrast agent can both be seen in the first image, the contrast agent is stated to be iodine injections; abstract; column 11, lines 2-34; column 20, lines 1-27), the second material is surrounding tissue (the second material is surrounding breast tissue in this example but would be applied to any biological tissue desired by adjusting parameters and weights of the reconstruction algorithms; abstract; column 11, lines 2-34; column 20, lines 1-27), the first image is constructed such that the at least one of the bones or the contrast agent are highlighted and such that information relating to the surrounding tissue is suppressed (healthcare provider may administer an X-ray contrast agent before taking a mammogram as an example, the healthcare provider can provide an iodine injection prior to taking the mammogram to aid in the visualization of blood vessels; column 20, lines 17-21), the second image is constructed such that the surrounding tissue is highlighted and such that information relating to the at least one of the bones or the contrast agent is suppressed (the computing system is adapted to determining a presence or absence of a medical feature in the medical imaging data, determining a presence of a cancerous spot in a mammography image by in part using a breast tissue diffraction pattern which allows the breast tissue to be highlighted in the second image seen in fig 6B, determining a severity of a feature in the data (e.g., determining the progression of a cancer), clustering data ( e.g., clustering images based on the presence or absence of a feature), predicting a presence or absence of a feature in new data (e.g., using previously acquired images to generate a prediction of a presence of a feature in a new set of data), or the like, or any combination thereof; fig 6B; column 20, lines 27-64; column 23, lines 2-51).
As per claim 5, LAZAREV discloses the method as claimed in claim 1, wherein the radiographs are recorded with an X-ray system that at least one of includes photon-counting detectors, includes a dual-layer detector, includes a multi-layer detector, records two consecutive images with different beam energies, or records two consecutive images with different filters (the x-ray device used includes multiple interchangeable filter which would be swapped for each image if desired, further the x-ray beam level is adjustable as the x-ray is provided as an adjustable collimation assembly allowing for the beam intensities to be adjusted; column 29, line 60-column 30, line 12).
As per claim 6, LAZAREV discloses the method as claimed in claim 1, wherein at least one of the first filter module or the second filter module includes at least one of a compressor configured to compress a dynamic range of an image, a feature enhancement filter, or a denoising filter, and the compressor and the feature enhancement filter are in series (radially integrating the provided filters can remove information about a distribution of the signals between axial and equatorial components, it can also improve signal to noise and provide a convenient way to display diffraction data and assists the filter in “denoising” the images; column 39, lines 1-50).
As per claim 7, LAZAREV discloses the method as claimed in claim 1, wherein the first filter module has different parameters from the second filter module, the first filter module is a same type of filter as the second filter module, and the first filter module and the second filter module have a same architecture (the computing system comprises adjustable algorithm weight and parameters to determine the image highlights and suppression, further the filter type may be interchangeable and also may be kept the same the user would select the type of filter suitable for the imaging being performed and the task identified and the filters would be the same if selected to be of the same material having the same spectral properties during the imaging process and since the filter is interchangeable it would have standard sizing (architecture) to fit the imaging device; abstract; figs 1, 2B, 9-10; column 13, lines 37-50; column 16, lines 20-50; column 17, lines 4-51; column 18, lines 20-39; column 21, lines 5-67).
As per claim 8, LAZAREV discloses an apparatus for post-processing radiographs from radiographic data including spectral recordings of a region of interest of an object (a computing system and method for post/preprocessing of radiographic x ray images and determine a region of interest of the radiographic images of a subject; abstract; figs 1, 9-10; column 21, lines 5-67; column 29, line 60-column 30, line 15), the apparatus comprising: an image unit configured to create, from the radiographs, a first image in which a first material of the object is highlighted and a second material of the object is suppressed (generating from the radiographic x-ray images a first image wherein cancer tissues is given a different diffraction pattern (highlighted) in order to differentiate the cancerous tissues that was identified from the other tissues and a second image wherein the breast tissues of the scan are more transparent and see through to further highlight the potentially cancerous tissues and is done by using transparent channels 90 of spectral energy from the radiograph/x-ray device and causes materials such as the filter, the compression plate, and bones are more opaque and transparent; abstract; figs 1, 2B, 9-10; column 17, lines 4-51; column 18, lines 20-39; column 21, lines 5-67), the first material having different spectral attenuation properties than the second material (the healthy breast tissue appearing more opaque and transparent than the cancerous tissues due to its different spectral properties when the x ray radiation and its beams are applied using the device; abstract; figs 1, 2B, 9-10; column 17, lines 4-51; column 18, lines 20-39; column 29, line 60-column 30, line 12), and create, from the radiographs, a second image in which the second material is highlighted and the first material is suppressed (using the radiographs the system is adapted to use/generate images of diffraction patterns which are the interactions of a radiation x-ray beam with a tissue and depending on the tissue type and its spectral properties appear differently in the image allowing the user to diagnose the tissue types and would allow for the healthy breast tissue to be highlighted and the cancerous tissue to be suppressed/made opaque/translucent based on adjustment of algorithm parameters and weights which control the radiography/x-ray device; abstract; figs 6A-6B; column 29, line 60-column 30, line 60; column 39, lines 1-50; column 40, lines 3-10); a post-processing unit configured to post-process the first image and the second image (), wherein the first image is post-processed by a first filter module and the second image is post-processed by a second filter module (the computing system applies post processing to the images by using filters, for example the collimated x-ray device uses a first filter made of molybdenum, rhodium, aluminum, copper, and/or tin filters and two dimensional detector, is used to generate the first image such that the breast tissue is opaque/transparent and cancerous tissue is highlighted, and further plate 12 is said to be transparent, the system to alter the image for image two would switch filter types to a filter with spectral/radiographic properties that would cause the healthy tissue of the breast to be highlighted and the cancerous tissues to be opaque or more transparent based on the radiation beams applied; NOTE; different radiograph filters of different materials can change how various tissues appear in an image by altering the energy spectrum of the X-ray beam before it reaches the patient and switching between two filter types would result in different tissues being highlighted in the respective images; abstract; figs 1, 2B, 9-10; column 16, lines 20-50; column 17, lines 4-51; column 18, lines 20-39; column 21, lines 5-67); a combining unit configured to combine the post-processed first image and the post-processed second image to form a single image in which the first material and the second material are depicted (using machine learning algorithms that are trained to detect presence of cancer use the x-ray, and radiograph images 6A as inputs in order to generate image 6B to determine known diseases in the tissue; fig 11; column 22, lines 15-35; column 39, lines 1-30); and an output unit configured to output the single image (the system is adapted to output figure 6b and a diagnosis indicator to the user; figs 6B and 11; column 6, lines 1-51; column 22, lines 15-35; column 39, line 50-column 40, line 10).
As per claim 9, LAZAREV discloses a control device configured to execute the method as claimed in claim 1 (a computer work station acting as the controller to control the imaging devices and conduct the method described; abstract; column 7, lines 43-64; claim 1).
As per claim 10, LAZAREV discloses a radiography system comprising the control device as claimed in claim 9 (the workstation computer controls and operates a computer radiograph and performs radiograph techniques; abstract; column 7, lines 43-64; column 33, lines 4-7; claim 1).
As per claim 11, LAZAREV discloses a non-transitory computer program product including instructions that, when executed by a computer, cause the computer to execute the method as claimed in claim 1 (the workstation computer comprises a memory and CPU to store and execute programs, data, and instructions related to the method described; column 25, lines 10-55).
As per claim 12, LAZAREV discloses a non-transitory computer-readable storage medium storing instructions that, when executed by a computer, cause the computer to perform the method of claim 1 (the workstation computer comprises a memory and CPU to store and execute programs, data, and instructions related to the method described; column 25, lines 10-55).
As per claim 14, LAZAREV discloses the method as claimed in claim 1, wherein at least one of the first filter module or the second filter module includes at least one of a compressor configured to compress a dynamic range of an image, a feature enhancement filter, or a denoising filter (radially integrating the provided filters can remove information about a distribution of the signals between axial and equatorial components, it can also improve signal to noise and provide a convenient way to display diffraction data and assists the filter in “denoising” the images; column 39, lines 1-50).
As per claim 15, LAZAREV discloses the method as claimed in claim 1, wherein the first filter module differs from the second filter module (the interchangeable filters would be interchanged for a filter of a different material type and different spectral properties to change the effect provided on the image; column 29, line 60-column 30, line 13).
As per claim 18, LAZAREV discloses the method as claimed in claim 16, wherein the first filter module has different parameters from the second filter module, the first filter module is a same type of filter as the second filter module, and the first filter module and the second filter module have a same architecture (the computing system comprises adjustable algorithm weight and parameters to determine the image highlights and suppression, further the filter type may be interchangeable and also may be kept the same the user would select the type of filter suitable for the imaging being performed and the task identified and the filters would be the same if selected to be of the same material having the same spectral properties during the imaging process; abstract; figs 1, 2B, 9-10; column 13, lines 37-50; column 16, lines 20-50; column 17, lines 4-51; column 18, lines 20-39; column 21, lines 5-67).
As per claim 19, LAZAREV discloses the method as claimed in claim 2, wherein at least one of the first filter module or the second filter module includes at least one of a compressor configured to compress a range of the image, a feature enhancement filter, or a denoising filter, and the compressor and the feature enhancement filter are in series (radially integrating the provided filters can remove information about a distribution of the signals between axial and equatorial components, it can also improve signal to noise and provide a convenient way to display diffraction data and assists the filter in “denoising” the images; column 39, lines 1-50).
As per claim 20, LAZAREV discloses the method as claimed in claim 2, wherein the first filter module has different parameters from the second filter module, the first filter module is a same type of filter as the second filter module, and the first filter module and the second filter module have a same architecture (the computing system comprises adjustable algorithm weight and parameters to determine the image highlights and suppression, further the filter type may be interchangeable and also may be kept the same the user would select the type of filter suitable for the imaging being performed and the task identified and the filters would be the same if selected to be of the same material having the same spectral properties during the imaging process and since the filter is interchangeable it would have standard sizing (architecture) to fit the imaging device; abstract; figs 1, 2B, 9-10; column 13, lines 37-50; column 16, lines 20-50; column 17, lines 4-51; column 18, lines 20-39; column 21, lines 5-67; column 29, line 60-column 30, line 13).
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.
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 non-obviousness.
Claims 3, and 16-17 are rejected under 35 § U.S.C. 103 as being obvious over US 12,588,883 B2 to LAZAREV et al. (hereinafter “LAZAREV”) in view of US 2019/0313993 A1 to ZHOU et al. (hereinafter “ZHOU”).
As per claim 3, LAZAREV discloses the method as claimed in claim 1. LAZAREV fails to disclose wherein, in a spectral recording of the region of interest, a plurality of raw images are available or created as the radiographs and the first image and the second image are calculated by a number of weighted subtractions of two of the plurality of raw images, wherein in each case a weighting factor defines which material is highlighted and which material is suppressed.
ZHOU discloses wherein, in a spectral recording of the region of interest, a plurality of raw images are available or created as the radiographs and the first image and the second image are calculated by a number of weighted subtractions of two of the plurality of raw images, wherein in each case a weighting factor defines which material is highlighted and which material is suppressed (the computing system is adapted to generate/capture raw images as x-ray images and radiograph images and further uses an objective function and is the weighted least square of the difference (subtraction) between the measure counts and the calculated counts wherein the computing/algorithm parameters are determined using said function; paragraphs [0033-0034], [0053-0056]; claim 6).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify LAZAREV to have in each case a weighting factor defines which material is highlighted and which material is suppressed of ZHOU reference. The Suggestion/motivation for doing so would have been to provide the ability to optimize the objective function to high light different tissues by changing the weights of said function allowing the system to be customized to various medical imaging tasks as suggested by ZHOU paragraphs [0053-0055]. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine ZHOU with LAZAREV to obtain the invention as specified in claim 3.
As per claim 16, LAZAREV discloses the method as claimed in claim 2. LAZAREV fails to disclose wherein, in a spectral recording of the region of interest, a plurality of raw images are available or created as the radiographs and the first image and the second image are calculated by a number of weighted subtractions of two of the plurality of raw images, wherein in each case a weighting factor defines which material is highlighted and which material is suppressed.
ZHOU discloses wherein, in a spectral recording of the region of interest, a plurality of raw images are available or created as the radiographs and the first image and the second image are calculated by a number of weighted subtractions of two of the plurality of raw images, wherein in each case a weighting factor defines which material is highlighted and which material is suppressed (the computing system is adapted to generate/capture raw images as x-ray images and radiograph images and further uses an objective function and is the weighted least square of the difference (subtraction) between the measure counts and the calculated counts wherein the computing/algorithm parameters are determined using said function; paragraphs [0033-0034], [0053-0056]; claim 6).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify LAZAREV to have wherein the filter in each case a weighting factor defines which material is highlighted and which material is suppressed of ZHOU reference. The Suggestion/motivation for doing so would have been to provide the ability to optimize the objective function to high light different tissues by changing the weights of said function allowing the system to be customized to various medical imaging tasks as suggested by ZHOU paragraphs [0053-0055]. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine ZHOU with LAZAREV to obtain the invention as specified in claim 16.
As per claim 17, LAZAREV in view of ZHOU discloses the method as claimed in claim 16. Modified LAZAREV further discloses wherein at least one of the first filter module or the second filter module includes at least one of a compressor configured to compress a dynamic range of an image, a feature enhancement filter, or a denoising filter, and the compressor and the feature enhancement filter are in series (radially integrating the provided filters can remove information about a distribution of the signals between axial and equatorial components, it can also improve signal to noise and provide a convenient way to display diffraction data and assists the filter in “denoising” the images; column 39, lines 1-50).
Claims 4 and 13 are rejected under 35 § U.S.C. 103 as being obvious over US 12,588,883 B2 to LAZAREV et al. (hereinafter “LAZAREV”) in view of US 2021/0267566 A1 to KONIG et al (hereinafter “KONIG”).
As per claim 4, LAZAREV discloses the method as claimed in claim 1. LAZAREV fails to disclose wherein the second image shows a decomposition of raw images in which a local contrast has been virtually replaced by water, wherein the local contrast includes at least one of a calcium contrast or a contrast agent contrast.
KONIG discloses wherein the second image shows a decomposition of raw images in which a local contrast has been virtually replaced by water, wherein the local contrast includes at least one of a calcium contrast or a contrast agent contrast (the computing system is adapted to capture raw images and then using the algorithmic comparison the forward projection or the vessels, which are segmented and contain contrast agent in the three-dimensional image data set, can be virtually replaced with water, so that the synthetic two-dimensional image only contains bone structures and the contrast is stated to be a contrast agent which is a iodine solution based on standard practice of the art; paragraphs [0011-0012], [0024]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify LAZAREV to have a local contrast has been virtually replaced by water of KONIG reference. The Suggestion/motivation for doing so would have been to provide the ability to only observe the bone structures of the image as suggested by paragraph [0024] of KONIG. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine KONIG with LAZAREV to obtain the invention as specified in claim 4.
As per claim 13, LAZAREV discloses the method as claimed in claim 1. LAZAREV fails to disclose wherein the second image shows a decomposition of raw images in which a local contrast has been virtually replaced by water.
KONIG discloses wherein the second image shows a decomposition of raw images in which a local contrast has been virtually replaced by water (the computing system is adapted to capture raw images and then using the algorithmic comparison the forward projection or the vessels, which are segmented and contain contrast agent in the three-dimensional image data set, can be virtually replaced with water, so that the synthetic two-dimensional image only contains bone structures; paragraphs [0011-0012], [0024]).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to modify LAZAREV to have a local contrast has been virtually replaced by water of KONIG reference. The Suggestion/motivation for doing so would have been to provide the ability to only observe the bone structures of the image as suggested by paragraph [0024] of KONIG. Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results. Therefore, it would have been obvious to combine KONIG with LAZAREV to obtain the invention as specified in claim 13.
Conclusion
Examiner's Note: Examiner has cited figures, and paragraphs in the references as applied to the claims above for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested for the applicant, in preparing the responses, to fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner. Examiner has also cited references in PTO892 but not relied on, which are relevant and pertinent to the applicant’s disclosure, and may also be reading (anticipatory/obvious) on the claims and claimed limitations. Applicant is advised to consider the references in preparing the response/amendments in-order to expedite the prosecution.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. These prior arts include the following:
US 2008/0310598 A1
US 9,848,844 B2
US 2016/0287205 A1
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DEVIN JACOB DHOOGE whose telephone number is (571) 270-0999. The examiner can normally be reached 7:30-5:00.
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/D J DHOOGE/Examiner, Art Unit 2677
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