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 .
Applicant’s Response
In Applicant’s Response dated 8/1/25, the Applicant amended Claims 1, 3, 4, 6, 8, canceled Claims 5 and 7, added Claim 9 and argued Claims previously rejected in the Office Action dated 4/22/25. Claims 1-4, 6, 8 and 9 are pending examination.
In light of the Applicant’s amendments and remarks, the rejections under 35 USC 101 and 112 have been withdrawn.
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Claim Interpretation
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.
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 in claim 1 including “an image acquisition section configured to acquire”, “an estimation section configured to estimate”, “a display control section configured to display”, in Claim 2 including “an alert output control section configured to set”.
If applicant does not intend to have these limitations interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitations to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitations recite sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 3, 4, 6, 8 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Espeland et al., United States Patent Publication 2022/0296081 (hereinafter “Espeland”), in view of Tomita et al., Attention-Based Deep Neural Networks for Detection of Cancerous and Precancerous Esophagus Tissue on Histopathological Slides (hereinafter “Tomita”) and Bernat et al., United States Patent Publication 20210042915 (hereinafter “Bernat”).
Claim 1:
Espeland discloses:
An image diagnosis apparatus, comprising:
an endoscopic image acquisition section configured to acquire an endoscope video obtained by capturing an esophagus of a subject (see paragraphs [0020]). Espeland teaches an endoscopic video data of an esophagus;
an estimation section configured to estimate a position of an esophageal cancer present in the endoscope video acquired by using a convolutional neural network trained as training data with an esophageal cancer image obtained by capturing an esophagus where an esophageal cancer is present (see paragraphs [0065]-[0069]). Espeland teaches determining, using a cnn, where cancer may be present in the esophagus; and
a display control section configured to display the position of the esophageal cancer estimated (see paragraphs [0020], [0024], [0069], [0075]). Espeland teaches displaying the images that possibly contain esophagus cancer and an indication of the detection scores. The detection signal may be in the form of a visual alert, e.g. displaying an indication of the one or more anatomical structure and/or one or more anatomical landmark on a display. For instance, a label can be used to indicate the presence and/or the location of the anatomical structure and/or landmark, either by overlaying the endoscopic video or separately from the endoscopic video, e.g. below it or next to it. The label can be in the form of a color code, a text, a sign or a shape. Alternatively, the detection signal may be in the form of an audio alert.
Espeland fails to expressly disclose training the CNN based on stained and non-stained images.
Tomita discloses:
wherein the convolutional neural network trained as training data with the esophageal cancer image is executed with the convolutional neural network coupled with a convolutional neural network trained as training data (see page 3, Methods, Dataset). Tomita teaches risk and precancer detection is based on training a CNN with multiple stained image and non-stained images of an esophagus. Tomita determines if precancerous tissue is present.
Accordingly, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include training a CNN on stained and non-stained images to determine precancerous detection risk for the purpose of effective and accurately detecting cancer, as taught by Tomita.
Espeland fails to expressly disclose a specific stain applied to the images.
Bernat discloses:
a convolutional neural network trained as training data with a multiple iodine unstained area esophagus image and a non-multiple iodine unstained area esophagus image, the multiple iodine unstained area esophagus image being a non-iodine staining image obtained by capturing an esophagus where a multiple iodine unstained area is present without performing iodine staining, the non-multiple iodine unstained area esophagus image being a non-iodine staining image obtained by capturing an esophagus where no multiple iodine unstained area is present without performing iodine staining (see paragraphs [0158], [0185]-[0189]). Bernat teaches a network being trained on multiple types of images in different categories and subcategories of interest including labeled images, unlabeled images. The images having stained images with areas that did not stain and areas that did stain to help determine the presence of cancer.
Accordingly, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include stained images and non-stained images to determine precancerous detection risk for the purpose of effective and accurately analyzing medical images using learned algorithms, as taught by Bernat.
Claim 3:
Espeland and Tomita fail to expressly disclose determining the presence or absence of iodine stain/unstained images.
Bernat discloses:
wherein the risk is determined based on estimation of presence or absence of a multiple iodine unstained area in the esophagus by using a convolutional neural network trained with a multiple iodine unstained area esophagus image and a non-multiple iodine unstained area esophagus image as training data, (see paragraphs [0158], [0185]-[0189]). Bernat teaches a network being trained on multiple types of images in different categories and subcategories of interest including labeled images, unlabeled images. The images having stained images with areas that did not stain and areas that did stain to help determine the presence of cancer.
Accordingly, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include stained images and non-stained images to determine precancerous detection risk for the purpose of effective and accurately analyzing medical images using learned algorithms, as taught by Bernat.
Claim 4:
Although Claim 4 is a method claim, it is interpreted and rejected for the same reasons as the apparatus of Claim 1.
Claim 6:
Although Claim 6 is a computer-readable medium claim, it is interpreted and rejected for the same reasons as the apparatus of Claim 1.
Claim 8:
Although Claim 8 is a computer-implemented learned model claim and being interested as a “computer program product”, it is interpreted and rejected for the same reasons as the apparatus of Claim 1.
Claim 9:
Espeland discloses:
wherein the display control section configured to display the position of the esophageal cancer and a degree of certainty indicating a possibility of presence of the esophageal cancer at the position on the endoscope video in a superimposed manner (see paragraphs [0020], [0024], [0069], [0075]). Espeland teaches displaying the images that possibly contain esophagus cancer and an indication of the detection scores. The detection signal may be in the form of a visual alert, e.g. displaying an indication of the one or more anatomical structure and/or one or more anatomical landmark on a display. For instance, a label can be used to indicate the presence and/or the location of the anatomical structure and/or landmark, either by overlaying the endoscopic video or separately from the endoscopic video, e.g. below it or next to it. The label can be in the form of a color code, a text, a sign or a shape. Alternatively, the detection signal may be in the form of an audio alert.
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Espeland, in view of Tomita and Bernat, in further view of Sidar et al., United States Patent Publication 2016/0235340 (hereinafter “Sidar”).
Claim 2:
Espeland discloses:
wherein the endoscope video is captured by inserting an endoscope capturing apparatus to the esophagus (see paragraph [0086]). Espeland teaches the endoscope being inserting into the body and esophagus; and
Espeland, Tomita and Bernat fail to expressly disclose an insertion speed of the endoscope system.
Sidar discloses:
wherein the image diagnosis apparatus further comprises an alert output control section configured to set a reference insertion speed of the endoscope capturing apparatus as an observation speed of a lumen of the esophagus corresponding to a risk of presence of an esophageal cancer in the esophagus, and output an alert upon a discrepancy between the reference insertion speed and an actual insertion speed (see paragraph [0035]). Sidar teaches alert the user when the speed of the tip of endoscope differs from the reference speed.
Accordingly, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the method disclosed by Espeland, Tomita and Bernat to include alert system when the speed of the endoscope differs from the reference speed for the purpose receiving accurate images, as taught by Sidar.
Response to Arguments
Applicant’s arguments, see REM, filed 8/22/25, with respect to the rejection of claim 1-4, 6, 8 and 9 under 35 USC 102 and 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new grounds of rejection is made in view of Espeland, in view of Tomita.
Claim Interpretation
The claims remain interpreted under 35 USC 112f because the claims recite the same language.
Claim Rejections – 35 USC 112
Claim 7 is rejected under 35 U.S.C. §112(b) or 35 U.S.C. §112 (pre-AlA), second paragraph, as allegedly being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Without conceding the propriety of the rejection, but rather as a part of cooperative efforts to expedite the prosecution of this application, Applicant has canceled Claim 7 without prejudice or disclaimer to address the rejection. Therefore, the rejection to Claim 7 is moot based on its cancellation. Withdrawal and reconsideration of the rejection under 35 U.S.C. §112(b) are respectfully requested.
The Examiner agrees and this rejection has been removed.
Claim Rejections – 35 USC 101
Applicant argues With respect to the rejection b), without conceding the propriety of the rejection, but rather as a part of cooperative efforts to expedite the prosecution of this application, Applicant has amended Claims 6 and 8 to overcome the rejection. At least in view of the current amendment, the rejection b) should be withdrawn and reconsidered.
The Examiner agrees and this rejection has been withdrawn.
Claim Rejection under 35 U.S.C. § 102 and 35 U.S.C. § 103
Applicant argues Accordingly, Tomita fails to teach or suggest “wherein the convolutional neural network trained as training data with the esophageal cancer image is executed with the convolutional neural network coupled with a convolutional neural network trained as training data with a multiple iodine unstained area esophagus image and a non-multiple iodine unstained area esophagus image, the multiple iodine unstained area esophagus image being a non-iodine staining image obtained by capturing an esophagus where a multiple iodine unstained area is present without performing iodine staining, the non-multiple iodine unstained area esophagus image being a non-iodine staining image obtained by capturing an esophagus where no multiple iodine unstained area is present without performing iodine staining,” as recited in amended Claim 1.
The Examiner agrees that Tomita does not teach Claim 1 and its entirety.
The Examiner introduced new art, Bernat, who teaches iodine staining images to determine which areas stain to identify if the cancer is present (see paragraph [0185]). Bernat also neural networks being trained on all types of image being categorized including stained images and unstained images.
Thus, Espeland teaches real-time detection of cancer in esophagus using endoscopic images, Tomita teaches training a CNN on stain images to identify the presence of cancer in the esophagus, and combining these arts with Bernat teaches training neural networks to identify the presence of cancer in iodine stain images and non-stained images to determine what portions the cancer exists, teaches the limitations of the independent claims, see the above rejections for the independent claims.
Applicant argues Claims 2-4, variously depend, directly or indirectly, from independent Claim 2. Espeland, Tomita, and Sidar are deficient with respect to Independent Claim 1, for at least the reasons stated above. Therefore, Applicant submits that Claims 2-4 are patentable over the proposed combination of references at least by virtue of their dependency, as well as the other features recited therein. Applicant, therefore, respectfully requests the reconsideration and withdrawal of rejections.
The Examiner agrees and new art is used to reject Claim 1.
See the above response to arguments with respect to Claim 1. For the same reasons listed above the rejections are not withdrawn but are rejected using new art.
Applicant argues Claim 9 depends from Claim 1, and thus, patentable over Espeland, Tomita, and Sidar for at least the reasons discussed above with respect to Claim 1, as well as for the additional features it recites. Accordingly, favorable consideration of new Claim 9 is respectfully requested.
The Examiner disagrees.
Espeland teaches displaying the images that possibly contain esophagus cancer and an indication of the detection scores. The detection signal may be in the form of a visual alert, e.g. displaying an indication of the one or more anatomical structure and/or one or more anatomical landmark on a display. For instance, a label can be used to indicate the presence and/or the location of the anatomical structure and/or landmark, either by overlaying the endoscopic video or separately from the endoscopic video, e.g. below it or next to it. The label can be in the form of a color code, a text, a sign or a shape. Alternatively, the detection signal may be in the form of an audio alert (see paragraphs [0020], [0024], [0069], [0075]). Thus, Espeland teaches the limitations of Claim 9.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. 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 mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TIONNA M BURKE whose telephone number is (571)270-7259. The examiner can normally be reached M-F 8a-4p.
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/TIONNA M BURKE/Examiner, Art Unit 2178 10/23/25
/STEPHEN S HONG/Supervisory Patent Examiner, Art Unit 2178
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