DETAILED ACTION
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 .
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 07/23/2026 has been entered.
Claim Rejections - 35 USC § 102
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.
Claims 1-18 are rejected under 35 U.S.C. 102(a1) as being anticipated by Conjeti et al. (Conjeti) (US 2022/0277444 A1).
Regarding claim 1, Conjeti discloses a computer-implemented method for providing at least one first metadata attribute of medical image data (e.g., A computer-implemented method is for providing at least one first metadata attribute associated with a medical image, Abstract), the method comprising:
receiving the medical image data and the at least one first metadata attribute, the at least one first metadata attribute including an attribute tag and a provisional attribute value (e.g., a step of receiving the medical image and the at least one first metadata attribute, wherein the at least one first metadata attribute comprises an attribute tag and a provisional attribute value, paragraph 11) and the medical image data including input data including at least one of information associated with a protocol, a study description, a series description, or a body region (e.g., the provisional attribute value can be filled in manually or automatically. In particular, the provisional attribute value can be filled in manually by a medical doctor and/or a medical assistant. Alternatively or additionally, the provisional attribute value can be filled in automatically by the medical imaging system. For example, the medical imaging system can fill in the provisional attribute value based on an imaging protocol, paragraph 82);
applying a first trained function to the medical image data to determine a standardized attribute value based on the input data (e.g., the method comprises applying a first trained function to the medical image so as to determine an image-based attribute value, paragraph 11);
determining a final attribute value based on the provisional attribute value and the standardized attribute value (e.g., In a further step, the method comprises determining a final attribute value based on the provisional attribute value and the image-based attribute value, paragraph 11); and
providing the at least one first metadata attribute, the at least one first metadata attribute including the attribute tag and the final attribute value (e.g., in a further step, the method comprises providing the at least one first metadata attribute, wherein the at least one first metadata attribute comprises the attribute tag and the final attribute value, paragraph 11).
Regarding claim 2, Conjeti discloses further comprising:
checking whether the provisional attribute value is in at least one of a standardized form or a standardized language, the determining determines the final attribute value based on the checking (e.g., Alternatively, the comparison can be based on a similarity-based comparison in order to determine if the provisional attribute value and the image-based attribute value are synonym to each other. If the provisional attribute value and the image-based attribute value are synonyms, the more general or the more standardized value can be set to be the final attribute value. In particular, the value corresponding to the ontology can be set to be the final attribute value, paragraph 102).
Regarding claim 3, Conjeti discloses wherein if the provisional attribute value is not in the at least one of the standardized form or the standardized language the determining includes, filling the final attribute value with the standardized attribute value (e.g., a further embodiment of the invention, if the provisional attribute value is empty, the step of determining the final attribute value comprises a step of filling the final attribute value with the image-based attribute value, paragraph 98).
Regarding claim 4, Conjeti discloses wherein at least one of the attribute tag or the provisional attribute value is associated with the protocol, the study description, the series description or the body region (e.g., the provisional attribute value can be filled in manually or automatically. In particular, the provisional attribute value can be filled in manually by a medical doctor and/or a medical assistant. Alternatively or additionally, the provisional attribute value can be filled in automatically by the medical imaging system. For example, the medical imaging system can fill in the provisional attribute value based on an imaging protocol, paragraph 82).
Regarding claim 5, Conjeti discloses wherein the applying includes, at least one of detecting or extracting the input data from the medical image data (e.g., The method comprises receiving input training data, wherein the input training data comprises a medical training-image and at least one first metadata training-attribute associated with the medical training-image, paragraph 158).
Regarding claim 6, Conjeti discloses wherein the applying includes,
translating the provisional attribute value into at least one of a standardized form or a standardized language (e.g., If the provisional attribute value and the image-based attribute value are synonyms, the more general or the more standardized value can be set to be the final attribute value. In particular, the value corresponding to the ontology can be set to be the final attribute value, paragraph 102).
Regarding claim 7, Conjeti discloses wherein
the first trained function comprises at least one of a natural language processing algorithm or is trained to understand at least one of grammatical rules, a meaning or a context (e.g., the third trained function can be based on a natural language processing technique like word embedding, word-level convolutional neural network, bi-direction long short-term memory network, recurrent neural network, dictionary learning and/or an image transformer network, paragraph 136), and
the determining the standardized attribute value includes analyzing or processing, by the first trained function, the medical image data based on the at least one of the natural language processing algorithm, the grammatical rules, the meaning or the context (e.g., the fourth trained function can be based on clinical named entity recognition. The fourth trained function can be based on a linguistic grammar technique using a natural language processing technique like word embedding, word-level convolutional neural network, bi-direction long short-term memory network, recurrent neural network and or dictionary learning, paragraph 142).
Regarding claim 8, Conjeti discloses wherein the medical image data are provided by a local system, and the checking is performed by the local system (e.g., at least one embodiment is directed to a unifying system for providing at least one metadata attribute associated with a medical image, paragraph 20).
Regarding claim 9, Conjeti discloses wherein the medical image data is provided by a local system, the local system provides the medical image data to a cloud system, the applying is performed by the cloud system (e.g., In the step of receiving the medical image and the at least one first metadata attribute, the medical image and the at least one first metadata attribute is received by an interface. The medical image and the at least one metadata attribute can be provided for example by a Picture Archiving and Communication System (PACS) or by a Radiology Imaging System (RIS) or by a Hospital Information System (HIS) etc, paragraph 83).
Regarding claim 10, claim 10 is a unifying system claim with limitations similar of limitations of claim 1. Therefore, claim 10 is rejected as set forth above as claim 1.
Regarding claim 11, claim 11 is a non-transitory computer program product claim with limitations similar of limitations of claim 1. Therefore, claim 11 is rejected as set forth above as claim 1.
Regarding claim 12, claim 12 is a non-transitory computer-readable medium claim with limitations similar of limitations of claim 1. Therefore, claim 12 is rejected as set forth above as claim 1.
Regarding claim 13, claim 13 is the method claim with limitations similar of limitations of claim 4. Therefore, claim 13 is rejected as set forth above as claim 4.
Regarding claim 14, claim 14 is the method claim with limitations similar of limitations of claim 5. Therefore, claim 14 is rejected as set forth above as claim 5.
Regarding claim 15, claim 15 is the method claim with limitations similar of limitations of claim 6. Therefore, claim 15 is rejected as set forth above as claim 6.
Regarding claim 16, claim 16 is the method claim with limitations similar of limitations of claim 7. Therefore, claim 16 is rejected as set forth above as claim 7.
Regarding claim 17, claim 17 is the method claim with limitations similar of limitations of claim 8. Therefore, claim 17 is rejected as set forth above as claim 8.
Regarding claim 18, claim 18 is the method claim with limitations similar of limitations of claim 9. Therefore, claim 18 is rejected as set forth above as claim 9.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to QUANG N VO whose telephone number is (571)270-1121. The examiner can normally be reached Monday-Friday, 7AM-4PM, EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Abderrahim Merouan can be reached at 571-270-5254. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/QUANG N VO/Primary Examiner, Art Unit 2683
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