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 Status
Applicant’s amendment filed on February 27, 2026 is acknowledged. Currently claims 1-6 and 8-21 are pending. Claims 1, 8, and 19 have been amended.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on December 04, 2025 is in compliance with the provisions of 27 CFR 1.97. Accordingly, the information disclosure statement is being considered and attached by the examiner.
Response to Arguments
Applicant’s arguments, filed February 27, 2026, with respect to independent claims 1, 8, and 19 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Kamon in view of Liu and Hofer.
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 nonobviousness.
Claims 1-6, 8-15, and 18-21 are rejected under 35 U.S.C. 103 as being unpatentable by Kamon et al., US 20210343011 A1, (hereinafter “Kamon”) in view of Liu et al., US 20080081981 A1, (hereinafter “Liu”) in further view of Hofer et al., US 20170020364 A1, (hereinafter “Hofer”).
Regarding claim 1, Kamon teaches a medical image processing device comprising:
a nonvolatile memory storing an image processing parameter ([0069] “A read only memory (ROM) 211 is a nonvolatile storage element (a non-transitory recording medium) and stores a computer-readable code of a program that causes the CPU 210 and/or the image processing unit 204 (a medical image processing apparatus, a computer) to execute various image processing methods.” wherein an image processing parameter is various image processing methods); and
an image processor configured to ([0073] “a programmable logic device (PLD) which is a processor whose circuit configuration is changeable after manufacturing, such as a field programmable gate array (FPGA).” wherein an image processor is a programmable logic device):
([0069] “A read only memory (ROM) 211 is a nonvolatile storage element (a non-transitory recording medium) and stores a computer-readable code of a program that causes the CPU 210 and/or the image processing unit 204 (a medical image processing apparatus, a computer) to execute various image processing methods.” wherein the image processing parameter is various image processing methods), and
execute image processing, by using the image processing parameter, on a captured image obtained by capturing a subject image ([0007] “To achieve the above-described object, a medical image processing apparatus according to a first aspect of the present invention includes a medical image acquiring unit that acquires a medical image from a medical apparatus that sequentially captures images of a plurality of areas in a living body of a subject”); and
a control circuit configured to control an operation of the image processor ([0068] “These processing operations are performed under control by a central processing unit (CPU) 210.” wherein a control circuit is a central processing unit) ([0073] “a programmable logic device (PLD) which is a processor whose circuit configuration is changeable after manufacturing, such as a field programmable gate array (FPGA).” wherein an image processor is a programmable logic device).
Kamon does not specifically disclose spontaneously read from the nonvolatile memory after power is turned on.
However, Liu teaches spontaneously read from the nonvolatile memory after power is turned on ([0030] “In this embodiment, a soft-core processor is used as the core of the control module, and programs of the soft-core processor and the logic design data of FPGA are saved in the nonvolatile memory. After the control panel is powered up, FPGA automatically read configuration data from this nonvolatile memory to complete the configuration of FPGA.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to substitute the nonvolatile memory of Kamon with a nonvolatile memory that can spontaneously read of Liu to reduce the load on the control circuit.
Kamon in view of Liu does not specifically disclose a lookup table used for the image processing and configuration data for configuring the image processor.
However, Hofer teaches a lookup table used for the image processing and configuration data for configuring the image processor ([0014] “In one embodiment of the invention, provision may be made for the configuration data to comprise at least one look-up table. Advantageous is here that converting the camera-head-specific information to associated configuration data is easily achievable. Alternatively or additionally, the configuration data can comprise at least one short code. The advantage here is that addressing configuration data which are to be provided to the image signal pre-processing unit is easily achievable.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include a lookup table and configuration data of Hofer in the medical image processing device of Kamon in view of Liu to enhance the performance optimization of image processing as well as increase storage efficiency.
Regarding claim 2, Kamon in view of Liu and Hofer teaches the medical image processing device according to claim 1, wherein the image processor is a programmable logic device (Kamon - [0073] “a programmable logic device (PLD) which is a processor whose circuit configuration is changeable after manufacturing, such as a field programmable gate array (FPGA).”).
The motivation for combining Kamon, Liu, and Hofer is the same motivation as used for claim 1.
Regarding claim 3, Kamon in view of Liu and Hofer teaches the medical image processing device according to claim 2, wherein the nonvolatile memory is configured to store the image processing parameter and a configuration data for the image processor (Liu - [0030] “In this embodiment, a soft-core processor is used as the core of the control module, and programs of the soft-core processor and the logic design data of FPGA are saved in the nonvolatile memory. After the control panel is powered up, FPGA automatically read configuration data from this nonvolatile memory to complete the configuration of FPGA.”) (Kamon - [0069] “the image processing unit 204 (a medical image processing apparatus, a computer) to execute various image processing methods.” wherein the image processing parameter is various image processing methods) (Kamon - [0073] “a programmable logic device (PLD) which is a processor whose circuit configuration is changeable after manufacturing, such as a field programmable gate array (FPGA).” wherein configuration data is circuit configuration and an image processor is a programmable logic device).
The motivation for combining Kamon, Liu, and Hofer is the same motivation as used for claim 1.
Regarding claim 4, Kamon in view of Liu and Hofer teaches the medical image processing device according to claim 1, wherein the medical image processing device includes a plurality of set, each set having a nonvolatile memory and an image processor (Liu - [0030] “In this embodiment, a soft-core processor is used as the core of the control module, and programs of the soft-core processor and the logic design data of FPGA are saved in the nonvolatile memory. After the control panel is powered up, FPGA automatically read configuration data from this nonvolatile memory to complete the configuration of FPGA.”) (Kamon - [0073] “a programmable logic device (PLD) which is a processor whose circuit configuration is changeable after manufacturing, such as a field programmable gate array (FPGA).” wherein an image processor is a programmable logic device) (Kamon - [0073] “The above-described functions of the individual units of the image processing unit 204 can be implemented by using various types of processors and a recording medium.”).
The motivation for combining Kamon, Liu, and Hofer is the same motivation as used for claim 1.
Regarding claim 5, Kamon in view of Liu and Hofer teaches the medical image processing device according to claim 1, wherein
the nonvolatile memory is configured to store a plurality of types of the image processing parameters corresponding to a plurality of types of operation modes in the medical image processing device (Liu - [0030] “In this embodiment, a soft-core processor is used as the core of the control module, and programs of the soft-core processor and the logic design data of FPGA are saved in the nonvolatile memory. After the control panel is powered up, FPGA automatically read configuration data from this nonvolatile memory to complete the configuration of FPGA.”) (Kamon - [0069] “a computer-readable code of a program that causes the CPU 210 and/or the image processing unit 204 (a medical image processing apparatus, a computer) to execute various image processing methods.” wherein an image processing parameter is various image processing methods) ([0053] “The endoscope 100 includes a handheld operation section 102 and an insertion section 104 that communicates with the handheld operation section 102.” wherein the medical image processing device is the endoscope), and
the image processor is configured to read out the image processing parameter corresponding to the operation mode of the medical image processing device from the nonvolatile memory (Kamon - [0073] “a programmable logic device (PLD) which is a processor whose circuit configuration is changeable after manufacturing, such as a field programmable gate array (FPGA).” wherein an image processor is a programmable logic device) (Kamon - [0069] “the image processing unit 204 (a medical image processing apparatus, a computer) to execute various image processing methods.” wherein the image processing parameter is various image processing methods) (Kamon - [0053] “The endoscope 100 includes a handheld operation section 102 and an insertion section 104 that communicates with the handheld operation section 102.” wherein the medical image processing device is the endoscope) (Liu - [0030] “In this embodiment, a soft-core processor is used as the core of the control module, and programs of the soft-core processor and the logic design data of FPGA are saved in the nonvolatile memory. After the control panel is powered up, FPGA automatically read configuration data from this nonvolatile memory to complete the configuration of FPGA.”), and
execute image processing on the captured image using the image processing parameter (Kamon - [0007] “To achieve the above-described object, a medical image processing apparatus according to a first aspect of the present invention includes a medical image acquiring unit that acquires a medical image from a medical apparatus that sequentially captures images of a plurality of areas in a living body of a subject”) (Kamon - [0069] “the image processing unit 204 (a medical image processing apparatus, a computer) to execute various image processing methods.” wherein the image processing parameter is various image processing methods).
The motivation for combining Kamon, Liu, and Hofer is the same motivation as used for claim 1.
Regarding claim 6, Kamon in view of Liu and Hofer teaches the medical image processing device according to claim 1, wherein
the nonvolatile memory is configured to store a plurality of types of the image processing parameters corresponding to a plurality of types of medical observation devices (Liu - [0030] “In this embodiment, a soft-core processor is used as the core of the control module, and programs of the soft-core processor and the logic design data of FPGA are saved in the nonvolatile memory. After the control panel is powered up, FPGA automatically read configuration data from this nonvolatile memory to complete the configuration of FPGA.”) (Kamon - [0069] “the image processing unit 204 (a medical image processing apparatus, a computer) to execute various image processing methods.” wherein the image processing parameter is various image processing methods) (Kamon - [0092] “As the “external device”, a device that observes an insertion area of the endoscope by using an electromagnetic wave, an ultrasonic wave, radiation, or the like can be used. In this case, the area estimating unit 232 (an area estimating unit) is capable of estimating an area by using information acquired by the external device (see the example illustrated in FIGS. 19A and 19B).” wherein medical observation devices are external devices), each of the medical observation devices being co figured to capture a subject image and generate the captured image (Kamon - [0092] “The area information acquiring unit 222 (an area information acquiring unit) acquires area information indicating an area in the living body whose endoscopic image has been captured (step S120: an area information acquisition step). The area information acquiring unit 222 is capable of acquiring the area information by analyzing the endoscopic image, by using area information input by the user, or by using information from an external device different from the medical image acquiring unit 220.” wherein a subject image is the area information and the captured image is the endoscopic image), and
the image processor (Kamon - [0073] “a programmable logic device (PLD) which is a processor whose circuit configuration is changeable after manufacturing, such as a field programmable gate array (FPGA).” wherein an image processor is a programmable logic device) is configured to
read out the image processing parameter corresponding to the medical observation device connected to the medical image processing device from the nonvolatile memory (Kamon - [0069] “the image processing unit 204 (a medical image processing apparatus, a computer) to execute various image processing methods.” wherein the image processing parameter is various image processing methods) (Kamon - [0092] “As the “external device”, a device that observes an insertion area of the endoscope by using an electromagnetic wave, an ultrasonic wave, radiation, or the like can be used. In this case, the area estimating unit 232 (an area estimating unit) is capable of estimating an area by using information acquired by the external device (see the example illustrated in FIGS. 19A and 19B).” wherein medical observation devices are external devices) (Liu - [0030] “In this embodiment, a soft-core processor is used as the core of the control module, and programs of the soft-core processor and the logic design data of FPGA are saved in the nonvolatile memory. After the control panel is powered up, FPGA automatically read configuration data from this nonvolatile memory to complete the configuration of FPGA.”), and
execute image processing on the captured image using the image processing parameter (Kamon - [0007] “To achieve the above-described object, a medical image processing apparatus according to a first aspect of the present invention includes a medical image acquiring unit that acquires a medical image from a medical apparatus that sequentially captures images of a plurality of areas in a living body of a subject”) (Kamon - [0069] “the image processing unit 204 (a medical image processing apparatus, a computer) to execute various image processing methods.” wherein the image processing parameter is various image processing methods).
The motivation for combining Kamon, Liu, and Hofer is the same motivation as used for claim 1.
Regarding claim 8, the claim recites similar limitations to claim 1 but in the form of a system. Therefore, claim 8 recites similar limitations to claim 1 and is rejected for similar rationale and reasoning (see the analysis for claim 1 above).
Regarding claim 9, Kamon in view of Liu and Hofer teaches the medical observation system according to claim 8, further comprising an input configured to receive a user operation to select one of the plurality of types of operation modes (Kamon - [0053] “An operator (a user) operates the handheld operation section 102 while grasping it and inserts the insertion section 104 into a body of a subject (a living body) to perform observation. The handheld operation section 102 is provided with an air/water supply button 141, a suction button 142, a function button 143 to which various functions are allocated, and an imaging button 144 for receiving an imaging instruction operation (a still image, a moving image).”).
The motivation for combining Kamon, Liu, and Hofer is the same motivation as used for claim 1.
Regarding claim 10, Kamon in view of Liu and Hofer teaches the medical observation system according to claim 9, wherein the control circuit is configured to output a control signal to the image processor to indicate the selected operation mode (Kamon - [0068] “These processing operations are performed under control by a central processing unit (CPU) 210.” wherein a control circuit is a central processing unit) (Kamon - [0068] “The configuration of the endoscope processor apparatus 200 will be described with reference to FIG. 2. In the endoscope processor apparatus 200, an image input controller 202 receives an image signal output from the endoscope 100, an image processing unit 204 (a medical image processing unit 234 or the like) performs necessary image processing thereon, and a video output unit 206 outputs a resulting image signal.”).
The motivation for combining Kamon, Liu, and Hofer is the same motivation as used for claim 1.
Regarding claim 11, Kamon in view of Liu and Hofer teaches the medical image processing device according to claim 4, wherein a first set of the plurality of sets includes a pre-processing image processor and a second set of the plurality of sets comprises a post-processing image processor (Kamon - [0078] “The intermediate layer 562B calculates a feature quantity through convolutional operation and pooling processing. The convolutional operation performed in the convolutional layer 564 is processing of acquiring a feature map through convolutional operation using a filter, and plays a role in feature extraction such as edge extraction from an image.” wherein a pre-processing image processor is executed by the intermediate layer) (Kamon - [0083] “The output layer 562C is a layer that detects the position of a region of interest depicted in an input medical image (a normal-light image, a special-light image) on the basis of the feature quantity output from the intermediate layer 562B and outputs the result thereof.” wherein a post-processing image processor is executed by the output layer).
The motivation for combining Kamon, Liu, and Hofer is the same motivation as used for claim 1.
Regarding claim 12, Kamon in view of Liu and Hofer teaches the medical image processing device according to claim 11, wherein the pre- processing image processor is configured to provide the captured image to the post-processing image processor after executing a first image processing (Kamon - [0078] “The intermediate layer 562B calculates a feature quantity through convolutional operation and pooling processing. The convolutional operation performed in the convolutional layer 564 is processing of acquiring a feature map through convolutional operation using a filter, and plays a role in feature extraction such as edge extraction from an image.” wherein a pre-processing image processor is executed by the intermediate layer) (Kamon - [0083] “The output layer 562C is a layer that detects the position of a region of interest depicted in an input medical image (a normal-light image, a special-light image) on the basis of the feature quantity output from the intermediate layer 562B and outputs the result thereof.” wherein a post-processing image processor is executed by the output layer).
The motivation for combining Kamon, Liu, and Hofer is the same motivation as used for claim 1.
Regarding claim 13, the claim recites similar limitations to claim 9 but in the form of a device. Therefore, claim 13 recites similar limitations to claim 9 and is rejected for similar rationale and reasoning (see the analysis for claim 9 above).
Regarding claim 14, the claim recites similar limitations to claim 10 but in the form of a device. Therefore, claim 14 recites similar limitations to claim 10 and is rejected for similar rationale and reasoning (see the analysis for claim 10 above).
Regarding claim 15, Kamon in view of Liu and Hofer teaches the medical image processing device according to claim 1, wherein the nonvolatile memory is configured to store a plurality of image processing parameter for use by the image processor for a corresponding plurality of medical observation devices used to capture the subject image (Liu - [0030] “In this embodiment, a soft-core processor is used as the core of the control module, and programs of the soft-core processor and the logic design data of FPGA are saved in the nonvolatile memory. After the control panel is powered up, FPGA automatically read configuration data from this nonvolatile memory to complete the configuration of FPGA.”) (Kamon - [0069] “the image processing unit 204 (a medical image processing apparatus, a computer) to execute various image processing methods.” wherein the image processing parameter is various image processing methods) (Kamon - [0007] “To achieve the above-described object, a medical image processing apparatus according to a first aspect of the present invention includes a medical image acquiring unit that acquires a medical image from a medical apparatus that sequentially captures images of a plurality of areas in a living body of a subject”).
The motivation for combining Kamon, Liu, and Hofer is the same motivation as used for claim 1.
Regarding claim 18, Kamon in view of Liu and Hofer teaches the medical image processing device according to claim 1, wherein the image processing includes at least one of optical black subtraction processing, demosaic processing, white balance adjustment processing, noise reduction processing, color correction processing, color enhancement processing, and contour enhancement processing (Kamon - [0098] “For example, an image captured by using white light (normal light) can be provided for recognition in the case of the stomach, and an image captured by using special light (blue narrow-band light), such as BLI (Blue Laser Imaging: registered trademark), can be provided for recognition in the case of the esophagus. In accordance with an area, an image captured by using special light, such as LCI (Linked Color Imaging: registered trademark), and subjected to image processing (in the case of LCI, a difference in chroma or hue of a color close to the color of the mucous membrane is extended) may be used.”).
The motivation for combining Kamon, Liu, and Hofer is the same motivation as used for claim 1.
Regarding claim 19, the claim recites similar limitations to claim 1 but in the form of a method. Therefore, claim 19 recites similar limitations to claim 1 and is rejected for similar rationale and reasoning (see the analysis for claim 1 above).
Regarding claim 20, the claim recites similar limitations to claim 17 but in the form of a method. Therefore, claim 20 recites similar limitations to claim 17 and is rejected for similar rationale and reasoning (see the analysis for claim 17 above).
Regarding claim 21, Kamon in view of Liu and Hofer teaches a non-transitory computer readable device having computer readable instructions that when executed by circuitry cause the circuitry to perform the method of claim 19 (Kamon - [0030] “In addition, a program that causes the medical image processing apparatus or a computer to execute the medical image processing method according to these aspects, and a non-transitory recording medium storing computer-readable code of the program are also included in an aspect of the present invention.”).
The motivation for combining Kamon, Liu, and Hofer is the same motivation as used for claim 1.
Claims 16 and 17 are rejected under 35 U.S.C. 103 as being unpatentable of Kamon et al., US 20210343011 A1, (hereinafter “Kamon”) in view of Liu et al., US 20080081981 A1, (hereinafter “Liu”) in further view of Hofer et al., US 20170020364 A1, (hereinafter “Hofer”) in further view of Duckett et al., US 20220026725 A1, (hereinafter “Duckett”).
Regarding claim 16, Kamon in view of Liu and Hofer teaches the medical image processing device according to claim 1, wherein the medical observation device includes a (Kamon - [0092] “As the “external device”, a device that observes an insertion area of the endoscope by using an electromagnetic wave, an ultrasonic wave, radiation, or the like can be used. In this case, the area estimating unit 232 (an area estimating unit) is capable of estimating an area by using information acquired by the external device (see the example illustrated in FIGS. 19A and 19B).” wherein medical observation devices are external devices).
Kamon in view of Liu and Hofer does not specifically disclose a camera head having a memory storing a camera head identifier.
However, Duckett teaches a camera head having a memory storing a camera head identifier ([0048] “The camera head can identify the endoscope being attached and store in memory or adjust automatically based on a detection of a specific endoscope type, where the variable liquid lens 20 or the relative positions of the sensors 18 are adjusted.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include a camera head with a memory of Duckett in the medical observation device of Kamon in view of Liu and Hofer, to identify and document the type of endoscope that is being used to adjust based on the specific endoscope type.
Regarding claim 17, Kamon in view of Liu, Hofer, and Duckett teaches the medical image processing device according to claim 16, wherein the control circuit configured to receive the camera head identifier from the camera head and provide the camera head identifier to the image processor (Kamon - [0068] “These processing operations are performed under control by a central processing unit (CPU) 210.” wherein a control circuit is a central processing unit) (Duckett - [0048] “The camera head can identify the endoscope being attached and store in memory or adjust automatically based on a detection of a specific endoscope type, where the variable liquid lens 20 or the relative positions of the sensors 18 are adjusted.”).
The motivation for combining Kamon, Liu, Hofer and Duckett is the same motivation as used for claim 16.
Conclusion
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 date of this final action.
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/AMANDA H PEARSON/Examiner, Art Unit 2666
/MING Y HON/Primary Examiner, Art Unit 2666
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