CTNF 18/724,012 CTNF 101555 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-8 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The device of claim 1 is directed to a machine, which is one of the statutory categories of invention, and passes Step 1: Statutory Category- MPEP § 2106.03. However, the following steps of Claim 1 recite limitations that constitute mental processes because they describe acts of observation, evaluation, and judgement that can practically be performed in the human mind, or by a human using pen and paper as a physical aid, therefore failing Step 2A Prong One. These acts are mental processes because a human can look at an image and identify a possible lesion candidate, select or designate regions of interest and comparison regions in the image, compare two image regions and decide whether one is blurred, and decide whether the image is suitable in view of the blur result. detect a lesion candidate from the endoscopic image and output a lesion candidate image including the lesion candidate; set a lesion area corresponding to the lesion candidate and a corresponding area corresponding to the lesion area, in the lesion candidate image; determine a blur of an image of the lesion area based on the image of the lesion area and an image of the corresponding area; determine suitability of the lesion candidate image based on a determination result of the blur. Claim 1 fails Step 2A Prong Two because the additional elements beyond the judicial exception, including a memory and processor that acquire an endoscopic image, do not integrate the judicial exception into a practical application. Acquiring an endoscopic image is insignificant extra-solution activity (MPEP § 2106.05(g)), and there are no improvements to the functioning of a computer or any other technology or technical field (MPEP § 2106.05(a)) as the memory and processor merely apply the abstract idea on a computer (MPEP § 2106.05(f)). Furthermore, the claim does not impose meaningful limits on the computer components such that they are tied to a particular machine; the additional elements are described at a high level of generality and can be implemented on any generic computing system (MPEP § 2106.05(b)). Claim 1 also fails Step 2B, as these additional elements are well-understood, routine, and conventional (WURC), adding nothing significantly more than the abstract idea itself (MPEP § 2106.07(a)((III)). Acquiring an image and using a memory and processor are all WURC (see MPEP § 2106.05(d)). Claims 7 and 8 contain this identical ineligible subject matter, with the only additional element beyond the judicial exception being a non-transitory computer-readable medium, which also does not integrate the judicial exception into a practical application (see claim 1 analysis above) and is WURC (see MPEP § 2106.05(d)). Therefore, they are rejected. Claim 3, 5, and 6 recite limitations that constitute mental processes because they describe acts of observation, evaluation, and judgement that can practically be performed in the human mind, or by a human using pen and paper as a physical aid, therefore failing Step 2A Prong One. In Claim 3, these acts are mental processes because a human can observe lesion positions and choose comparison areas based on that position. In Claim 5, these acts are mental processes because determining the cause of unsuitability is a judgement/evaluation that a human can perform. In Claim 6, these acts are mental processes because a human can use pen and paper to write down a message displaying why a lesion candidate is unsuitable. These claims, alongside claims 2 and 4, also fail Step 2A Prong Two and Step 2B because the additional elements beyond the judicial exception do not integrate the judicial exception into a practical application and are WURC (see claim 1 analysis above); therefore, they are rejected. Claim Rejections - 35 USC § 102 07-07-aia AIA 07-07 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 – 07-08-aia AIA (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. 07-12-aia AIA (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. 07-15 AIA Claim s 1-8 are rejected under 35 U.S.C. 102 ( a)(1 ) as being anticipated by Masuno (JP7637683B2) . Regarding Claim 1, Masuno teaches an image determination device comprising: Paragraph [0048]: “The image determination unit 72 analyzes the input endoscopic image and performs a determination process to determine whether or not the input endoscopic image satisfies a predetermined standard required for the recognition processing (analysis performed by the recognition processing unit 70).” a memory configured to store instructions; Paragraph [0036]: “The central control unit 68 is a hardware resource for executing program instructions stored in a memory 69, and drives and controls each unit of the processor device 16 to execute the program instructions .” and a processor configured to execute the instructions to (Paragraph [0036] (shown above)): acquire an endoscopic image; Paragraph [0037]: “The image acquisition unit 50 acquires an endoscopic image input from the endoscope 12 .” detect a lesion candidate from the endoscopic image and output a lesion candidate image including the lesion candidate; Paragraph [0045]: “In the detection process, it is determined whether each small region is a lesion based on the calculated features, a group of regions identified as the same type is extracted as one lesion, and a region including the extracted lesion is detected as a region of interest .” set a lesion area corresponding to the lesion candidate and a corresponding area corresponding to the lesion area, in the lesion candidate image; Paragraph [0045]: “In the discrimination process, the type and/or degree (stage) of the lesion is determined for the detected region of interest based on the features in the region of interest and the state (position, size, shape, etc.) of the region of interest .” Explanation: Setting lesion area and spatial correspondence is shown through defining region of interest and its properties. determine a blur of an image of the lesion area based on the image of the lesion area and an image of the corresponding area; Paragraph [0050]: “When the amount of image blur is set as the predetermined criterion , as shown in Fig. 5, the image judgment unit 72 analyzes the endoscopic image to be judged and calculates an index value related to the amount of image blur (the larger the value, the larger the amount of image blur) .” Explanation: Blur is computed from image data (covers lesion/ROI and image context). determine suitability of the lesion candidate image based on a determination result of the blur. Paragraph [0050]: Then, the image judgment unit 72 compares the calculated index value with a preset threshold value for image blur judgment , and if the calculated index value is equal to or greater than the threshold value, i.e., if the amount of image blur is equal to or greater than a predetermined amount of blur, it judges that the predetermined criterion is not met . On the other hand, if the calculated index value is less than the threshold value for image blur judgment, it judges that the predetermined criterion is met .” Explanation: Suitability = whether criteria is satisfied Regarding Claim 2, Masuno teaches the image determination device according to claim 1, wherein the processor determines the blur of the image of the lesion area based on power of high frequency component for each of the image of the lesion area and the image of corresponding area. Paragraph [0065]: “If it is judged that the predetermined criterion is not met with respect to the degree of focus (if the high frequency components of the image are below the criterion ) …” Explanation: Since high-frequency components correspond to image sharpness, and a reduction in high-frequency components corresponds to increased blur, this teaching determines blur based on high-frequency components (low high-frequency -[Wingdings font/0xE0] low focus -[Wingdings font/0xE0] high blur and vice versa). In addition, evaluating whether high-frequency components fall below a threshold requires assessing the magnitude (power) of those components. Regarding Claim 3, Masuno teaches the image determination device according to claim 2, wherein the processor sets one or more corresponding areas in a lower part of the lesion candidate image when there is the lesion candidate in an upper part of the lesion candidate image, and sets one or more corresponding areas in the upper part of the lesion candidate image when there is the lesion candidate in the lower part of the lesion candidate image. Paragraph [0045]: “In the recognition process, for example, an endoscopic image is divided into a plurality of small regions , and image features are calculated from the divided endoscopic image. In the detection process , it is determined whether each small region is a lesion based on the calculated features , a group of regions identified as the same type is extracted as one lesion, and a region including the extracted lesion is detected as a region of interest . In the discrimination process, the type and/or degree (stage) of the lesion is determined for the detected region of interest based on the features in the region of interest and the state (position, size, shape, etc.) of the region of interest .” Paragraph [0056]: “When the position of the area of interest is set as the predetermined criterion, as shown in Fig. 11, the image determination unit 72 detects the position (center position) of the area of interest detected in the recognition process and calculates the distance between the detected position and the center of the endoscopic image .” Explanation: Region of interest position is explicitly known, and corresponding regions are selected based on spatial relationship. The reference also explicitly detects lesion regions (areas of interest), determines their position within the image, and uses that position relative to the image (center/spatial layout). Dividing the image into regions and determining their position supports upper vs lower regions, and selecting or referencing other regions based on position corresponds to “corresponding areas.” Regarding Claim 4, Masuno teaches the image determination device according to claim 3, wherein the processor determines the blur of the image of the lesion area using a corresponding area that has a largest difference in the power of high frequency component between the lesion area and the corresponding area when there is a plurality of the corresponding area. Paragraph [0045]: “In the recognition process, for example, an endoscopic image is divided into a plurality of small regions , and image features are calculated from the divided endoscopic image. Paragraph [0050]: “When the amount of image blur is set as the predetermined criterion , as shown in Fig. 5, the image judgment unit 72 analyzes the endoscopic image to be judged and calculates an index value related to the amount of image blur (the larger the value, the larger the amount of image blur) .” Paragraph [0065]: “If it is judged that the predetermined criterion is not met with respect to the degree of focus (if the high frequency components of the image are below the criterion ) …” Explanation: The reference explicitly uses high-frequency components to evaluate focus/blur and computes feature values across multiple regions. This supports comparing lesion vs other regions and selecting regions based on differences (e.g., largest difference). Regarding Claim 5, Masuno teaches the image determination device according to claim 1, wherein the processor is further configured to calculate light quantity of the image of the lesion area and the image of the corresponding area, wherein the processor determines cause why the lesion candidate image is unsuitable based on the determination result of the blur and a determination result of the light quantity. Paragraph [0010]: “The brightness of the endoscopic image may be set as the predetermined criterion, and if the brightness is equal to or lower than the predetermined criterion, it may be determined that the predetermined criterion is not met .” Paragraph [0051]: “The predetermined criterion is not limited to the amount of image blur . The predetermined criterion may be the degree of focus, image brightness , halation, adhesion, feature amount, or attention area position.” Paragraph [0052]: “When the image luminance is set as the predetermined criterion, as shown in Fig. 7, the image determination unit 72 analyzes the endoscopic image to be determined and detects the image luminance ( for example, the average luminance gradation value of each pixel of the entire image or the region of interest ).” Paragraph [0058]: “Here, as the primary criterion, one or more of the above-mentioned image blur amount, focus degree, image brightness, halation, attachment, feature amount, and attention area position are set, and it is determined that the primary criterion is satisfied when all of these are satisfied or a predetermined ratio or more is satisfied .” Paragraph [0065]: “The contents of advice in the advice process (the contents of the message for advice) are preferably determined with reference to the cause of the judgment that the predetermined criterion is not met .” Regarding Claim 6, Masuno teaches the image determination device according to claim 5, wherein the processor is further configured to display an unsuitable lesion candidate image and a message indicating the cause why the lesion candidate image is unsuitable. Paragraph [0044]: “The detailed observation mode image processing unit 64 also performs image processing similar to that performed by the normal observation mode processing unit, and the processed endoscopic image is displayed on the display 18 .” Paragraph [0065]: “The contents of advice in the advice process (the contents of the message for advice) are preferably determined with reference to the cause of the judgment that the predetermined criterion is not met . In this case, for example, if it is judged that the predetermined criterion is not met with respect to the amount of image blur, a message is displayed urging the user to "move the camera (the tip 12d of the insertion section 12a) slowly ". If it is judged that the predetermined criterion is not met with respect to the degree of focus (if the high frequency components of the image are below the criterion), a message is displayed urging the user to "move the camera (the tip 12d of the insertion section 12a) back and forth" so that the image is in focus . If it is judged that the predetermined criterion is not met with respect to image brightness, a message is displayed urging the user to "increase the amount of illumination light" or "accurately apply illumination light to the object of observation" .” Regarding Claim 7, Masuno teaches all of the limitations of claim 1 above because claim 7 recites a method that performs substantially the same steps as claim 1. Regarding Claim 8, Masuno teaches all of the limitations of claim 1 above because claim 8 recites a non-transitory computer-readable recording medium storing a program that causes a computer to execute processing that performs the same steps as claim 1. Paragraph [0069]: “As an example of configuring multiple processing units with one processor , first, as represented by a computer such as a client or server , there is a form in which one processor is configured with a combination of one or more CPUs and software, and this processor functions as multiple processing units .” Explanation: This corresponds to a non-transitory computer-readable medium, that, when executed, performs the recited processing . Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Shiratani (US2020342598A1) teaches an image diagnosis support system that includes: an input unit that receives an input of an image; a specifying unit that specifies a specular reflection region and a non-specular reflection region in a region of interest in the image; and a determination unit that determines whether the region of interest is an inadequate region that is inadequate for diagnosis on the basis of an image processing result for at least one of the specular reflection region and the non-specular reflection region. It would also render a 102 rejection for claims 1, 2, 7, and 8. Iwasaki (JP2017213097A) teaches an image processing device, an image processing method, and a program that enables reliability of a detection result on a lesion candidate region to be grasped. It would also render a 102 rejection for claims 1, 2, 6, 7, and 8. 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If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /WILLIAM ADU-JAMFI/Examiner, Art Unit 2677 /ANDREW W BEE/Supervisory Patent Examiner, Art Unit 2677 Application/Control Number: 18/724,012 Page 2 Art Unit: 2677 Application/Control Number: 18/724,012 Page 3 Art Unit: 2677 Application/Control Number: 18/724,012 Page 4 Art Unit: 2677 Application/Control Number: 18/724,012 Page 5 Art Unit: 2677 Application/Control Number: 18/724,012 Page 6 Art Unit: 2677 Application/Control Number: 18/724,012 Page 7 Art Unit: 2677 Application/Control Number: 18/724,012 Page 8 Art Unit: 2677 Application/Control Number: 18/724,012 Page 9 Art Unit: 2677 Application/Control Number: 18/724,012 Page 10 Art Unit: 2677
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