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 .
Claim Rejections - 35 USC § 101
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a Judicial Exception in the form of an Abstract Idea, without significantly more:
Beginning with independent claim 1, a process claim, which recites:
A method for determining a cutaneous lesion score of a companion animal suspected to have an atopic dermatitis condition, using an assessment module trained beforehand to learn features indicative of an atopic dermatitis condition in a companion animal, based at least on a plurality of previously acquired images of companion animal body surfaces, some of these images having cutaneous lesion(s), the method comprising at least the steps of: a) receiving companion animal data corresponding to said companion animal, wherein the companion animal data include at least one global lesions image of said companion animal, and at least one metadata relative to said companion animal, b) operating said trained assessment module on the companion animal data, and c) based on said assessment module, generating a cutaneous lesion score indicative of at least one cutaneous state of said companion animal.
The claim recites abstract ideas:
“receiving” and “generating” are mere data gathering and output recited at a high level of generality, and thus are insignificant extra-solution activity.
A process that encompass a human performing the steps mentally with or without a physical aid in the form of the “generating” steps, with the “receiving” step and “operating” step being pre-solution acts of processing information which could be performed visually and/or mentally; and
A method of organizing human behavior in the form of a social activity of following rules or instructions informing a person to perform the “receiving” step, “operating” and the “generating” step
These two abstract ideas will be considered together for analysis as a single abstract idea per MPEP 2106:
PNG
media_image1.png
468
1527
media_image1.png
Greyscale
Independent claim 14, a process claim, which recites:
A device for determining a cutaneous lesion score of a companion animal suspected to have an atopic dermatitis condition, the device comprising an assessment module trained beforehand to learn features indicative of an atopic dermatitis condition in a companion animal, based at least on a plurality of previously acquired images of companion animal body surfaces, some of these images having cutaneous lesion(s), said trained assessment module being configured to operate on the companion animal data wherein the companion animal data includes at least one lesions global image of said companion animal body surface, and at least one metadata relative to said companion animal, and to generate a cutaneous lesion score indicative of at least one cutaneous state of said companion animal.
The claim recites abstract ideas:
“training” explicitly recites performing mathematical calculations, the limitation falls within the “mathematical concepts” grouping of abstract ideas.
A process that encompass a human performing the steps mentally with or without a physical aid in the form of the “training” steps, with the “extracting” step and “associating” step being pre-solution acts of processing information which could be performed visually and/or mentally; and
A method of organizing human behavior in the form of a social activity of following rules or instructions informing a person to perform the “extracting” step and “associating” step and the “training” step
These two abstract ideas will be considered together for analysis as a single abstract idea per MPEP 2106:
PNG
media_image1.png
468
1527
media_image1.png
Greyscale
Independent claim 16, a device claim, which recites:
A device for determining a cutaneous lesion score of a companion animal suspected to have an atopic dermatitis condition, the device comprising an assessment module trained beforehand to learn features indicative of an atopic dermatitis condition in a companion animal, based at least on a plurality of previously acquired images of companion animal body surfaces, some of these images having cutaneous lesion(s), said trained assessment module being configured to operate on the companion animal data wherein the companion animal data includes at least one lesions global image of said companion animal body surface, and at least one metadata relative to said companion animal, and to generate a cutaneous lesion score indicative of at least one cutaneous state of said companion animal
The claim recites abstract ideas:
An device having the trained assessment module performing “operating” step and the “generating” steps is considered being performed by a generic computer. In addition, the limitation does it does not provide any details about how the “operating” step and the “generating” step are performed. Therefore, If the apparatus, processor and memory are removed from the claim, the method can be easily performed by a human being without the need of any of a computer component. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
A process that encompass a human performing the steps mentally with or without a physical aid in the form of the “operating” step and the “generating” step being pre-solution acts of processing information which could be performed visually and/or mentally; and
A method of organizing human behavior in the form of a social activity of following rules or instructions informing a person to perform the “operating” step and the “generating” step.
These two abstract ideas will be considered together for analysis as a single abstract idea per MPEP 2106:
PNG
media_image1.png
468
1527
media_image1.png
Greyscale
Beginning with independent claim 18, a process claim, which recites:
Computer program product for determining a cutaneous lesion score of a companion animal suspected to have an atopic dermatitis condition, using an assessment module trained beforehand to learn features indicative of an atopic dermatitis condition in a companion animal, based at least on a plurality of previously acquired images of companion animal body surfaces, some of these images having cutaneous lesion(s), the computer program product comprising a support and stored on this support instructions that can be read by a processor, these instructions being configured to: a) receiving companion animal data corresponding to said companion animal, wherein the companion animal data includes at least one lesions global image of said companion animal body surface, and at least one metadata relative to said companion animal, b) operating said trained assessment module on the companion animal data, andc) based on said assessment module, generating a cutaneous lesion score indicative of at least one cutaneous state of said companion animal.
The claim recites abstract ideas:
“receiving” and “generating” are mere data gathering and output recited at a high level of generality, and thus are insignificant extra-solution activity.
A process that encompass a human performing the steps mentally with or without a physical aid in the form of the “generating” steps, with the “receiving” step and “operating” step being pre-solution acts of processing information which could be performed visually and/or mentally; and
A method of organizing human behavior in the form of a social activity of following rules or instructions informing a person to perform the “receiving” step, “operating” and the “generating” step
These two abstract ideas will be considered together for analysis as a single abstract idea per MPEP 2106:
PNG
media_image1.png
468
1527
media_image1.png
Greyscale
This judicial exception is not integrated into a practical application because there are no recited additional elements that amount to a practical application, such as but no limited to the following as noted in MPEP 2106:
PNG
media_image2.png
453
1451
media_image2.png
Greyscale
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception for the same reason: There are not additional elements other than the abstract idea.
Independent claims 1, 14, 16 and 18 are merely a generic computer implementation of the abstract ideas and likewise do not amount to significantly more. See MPEP 2106:
PNG
media_image3.png
249
1434
media_image3.png
Greyscale
Likewise, the following dependent claims have been analyzed and do not recite elements that recite a practical application or significantly more and remain rejected under 35 USC 101: Claims 2-13, 15, 17 and 19-20.
Claim Rejections - 35 USC § 101
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 18-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
A computer program is merely a set of instructions capable of being implemented by a computer. However, by itself without being encoded onto a non-transitory computer-readable medium is not realizable. Hence, claim 16 contains merely nonstatutory functional descriptive material. See MPEP 2106: IV(B)(1)(a), last paragraph.
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.
Claims 14 and 15 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by
EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis.
With respect to claim 14, EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis teaches a method for training an assessment module to learn features indicative of an atopic dermatitis condition in a companion animal, using at least a plurality of previously acquired images of companion animal body surfaces, some of these images having cutaneous lesion(s) [biologically and scientifically, humans are animals (Section 2, Data)], the method comprising:
- extracting at least one lesion feature from each previously acquired image (Section 2, Data),
- associating at least said image and said at least one lesion feature to an animal cutaneous state (Section 2, Data), and
- training the assessment module to learn said association (Section 2, Data).
With respect to claim 15, which further limits claim 14, EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis teaches wherein, said assessment module comprising at least one neural network, the method comprising the step of updating weights of the neural network according to said association between said at least one lesion feature and said animal cutaneous state [when the severity network is being trained, the severity network is considered being updated weights of the severity network (Section 2, Data)].
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.
Claims 1-3, 5-10, 13 and 16-20 are rejected under 35 U.S.C. 103 as being unpatentable over EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis and further in view of Frosch’933 (US 2021/0158933).
With respect to claim 1, EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis teaches a method for determining a cutaneous lesion score of a companion animal suspected to have an atopic dermatitis condition, using an assessment module trained beforehand to learn features indicative of an atopic dermatitis condition in a companion animal, based at least on a plurality of previously acquired images of companion animal body surfaces, some of these images having cutaneous lesion(s) [determining the human skin diseases is considered as determining the animal skin diseases (abstract section and introduction section). In addition, biologically and scientifically, humans are animals], the method comprising at least the steps of:
a) receiving companion animal data corresponding to said companion animal, wherein the companion animal data include at least one global lesions image of said companion animal [Our data originates from the Softened Water Eczema Trial (SWET), which is a randomised controlled trial of 12 weeks duration followed by a 4-week crossover period, for 310 AD children aged from 6 months to 16 years. The original
data contains 1393 photos of representative AD regions taken during their clinic
visits, along with the corresponding severity of each disease sign. During each
visit, a disease assessment was made for SASSAD and TISS, using the 7 disease
signs labelled for each image. The severity of each sign was determined on an
ordinal scale: none (0), mild (1), moderate (2), or severe (3) (Section 2, Data).],
b) operating said trained assessment module on the companion animal data [During each visit, a disease assessment was made for SASSAD and TISS, using the 7 disease
signs labelled for each image (Section 2, Data and Fig.2)], and
c) based on said assessment module, generating a cutaneous lesion score indicative of at least one cutaneous state of said companion animal [Finally, the predictions for the disease signs are combined to produce a probability distribution of the regional severity scores (SASSAD,TISS and EASI) per image (section 3.2 Severity Prediction and Fig.2).].
EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis does not teach the companion animal data includes at least one metadata relative to said companion animal.
Frosch’933 teaches that teach the companion animal data includes at least one metadata relative to said companion animal (paragraph 39).
Therefore, 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 the invention of EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis according to the teaching of Frosch’933 to include metadata in original data for identifying the age the humans associated with the original data because this will allow the severity prediction network to be trained more effectively.
With respect to claim 2, which further limits claim 1, EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis teaches wherein said at least one global lesions image comprise at least one image of the underside body surface of said companion animal [as shown in Fig.2, an image of a foot of a human is being received for obtaining the probabilistic predictions for each disease].
With respect to claim 3, which further limits claim 1, EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis teaches wherein said companion animal data further comprise at least one lesion specific image of a cutaneous lesion of said companion animal [as shown in Fig.2, an image of a foot of a human is being received for obtaining the probabilistic predictions for each disease].
With respect to claim 5, which further limits claim 1, EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis does not teach wherein said at least one meta data relative to said companion animal includes animal data such as breed, species, activity level, medical history, reproductive status, age, gender, weight, spayed or neutered status, a biological value from a biological sample, body condition, health status, lifestyle, habitat, coat information, or risk factor, and/or medical data, such as the age of disease onset, the existence of previous episodes of hotspots, urticaria or angioedema, the presence of cortico-response pruritus, the excess of hair loss, scaling or dryness, gastrointestinal signs, an indication on whether or not symptoms worsen after walking in grass, or medical history of chronic and/or recurrent dermatoses or otitis.
Frosch’933 teaches wherein said at least one meta data relative to said companion animal includes animal data such as breed, species, activity level, medical history, reproductive status, age (paragraph 39), gender, weight, spayed or neutered status, a biological value from a biological sample, body condition, health status, lifestyle, habitat, coat information, or risk factor, and/or medical data, such as the age of disease onset, the existence of previous episodes of hotspots, urticaria or angioedema, the presence of cortico-response pruritus, the excess of hair loss, scaling or dryness, gastrointestinal signs, an indication on whether or not symptoms worsen after walking in grass, or medical history of chronic and/or recurrent dermatoses or otitis.
Therefore, 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 the invention of EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis according to the teaching of Frosch’933 to generate metadata from original data for identifying the age the humans associated with the original data because this will allow the severity prediction network to be trained more effectively.
With respect to claim 6, which further limits claim 1, EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis does not teach using a plurality of metadata relative to said companion animal, and especially comprising the step of providing a pathological profile of said companion animal based on said plurality of metadata.
Frosch’933 teaches using a plurality of metadata relative to said companion animal, and especially comprising the step of providing a pathological profile of said companion animal based on said plurality of metadata (paragraph 39).
Therefore, 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 the invention of EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis according to the teaching of Frosch’933 to generate metadata from original data for identifying the age the humans associated with the original data because this will allow the severity prediction network to be trained more effectively.
With respect to claim 7, which claim 1, EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis teaches wherein said assessment module uses a predictive model, comprising an object detection model, a neural network, especially a convolutional neural network, and a metadata encoding module (section, Introduction).
With respect to claim 8, which further limits claim 7, EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis teaches wherein said object detection model performs a recognition analysis on said at least one lesion image to reference said at least one cutaneous lesion (section, Introduction), one or more lesion features being especially referenced, such as spatial features, as the origin coordinates, the height, and/or the width.
With respect to claim 9, which further limits claim 6, EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis teaches wherein said neural network is trained beforehand to recognize cutaneous states of companion animals based at least on one lesion feature extracted from said plurality of previously acquired images of companion animal body surfaces (Fig. 2).
With respect to claim 10, which further limits claim 9, EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis teaches wherein said generated score depends at least on an assessed correlation between said lesion features and said lesion image (Fig.2).
With respect to claim 13, which further limits claim1, EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis teaches wherein said areas of said companion animal body surface are chosen among the head, especially the ear, perioral and/or periocular areas, the legs, especially the front feet (Fig.2) and/or the interdigital areas, the flexor surface of the tarsal joint and/or the extensor surface of the carpal joint, and the trunc, especially the groin, armpit, ventral and/or perineal areas.
With respect to claim 16, EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis teaches a device for determining a cutaneous lesion score of a companion animal suspected to have an atopic dermatitis condition [regarding to the system shown in Fig.2, In addition, biologically and scientifically, humans are animals],
the device comprising an assessment module trained beforehand to learn features indicative of an atopic dermatitis condition in a companion animal, based at least on a plurality of previously acquired images of companion animal body surfaces, some of these images having cutaneous lesion(s) (Section 2, Data),
said trained assessment module being configured to operate on the companion animal data wherein the companion animal data includes at least one lesions global image of said companion animal body surface [Our data originates from the Softened Water Eczema Trial (SWET), which is a randomised controlled trial of 12 weeks duration followed by a 4-week crossover period, for 310 AD children aged from 6 months to 16 years. The original data contains 1393 photos of representative AD regions taken during their clinic visits, along with the corresponding severity of each disease sign. During each visit, a disease assessment was made for SASSAD and TISS, using the 7 disease signs labelled for each image. The severity of each sign was determined on an ordinal scale: none (0), mild (1), moderate (2), or severe (3) (Section 2, Data).],
to generate a cutaneous lesion score indicative of at least one cutaneous state of said companion animal [Finally, the predictions for the disease signs are combined to produce a probability distribution of the regional severity scores (SASSAD,TISS and EASI) per image (section 3.2 Severity Prediction and Fig.2).].
EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis does not teach the companion animal data includes at least one metadata relative to said companion animal.
Frosch’933 teaches that teach the companion animal data includes at least one metadata relative to said companion animal (paragraph 39).
Therefore, 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 the invention of EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis according to the teaching of Frosch’933 to include metadata in original data for identifying the age the humans associated with the original data because this will allow the severity prediction network to be trained more effectively.
With respect to claim 17, which further limits claim 16, EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis teaches an acquisition module for acquiring said at least one lesion image of said companion animal body surface (Fig.2).
With respect to claim 18, it is a program claim which is being rejected for the same manner as described in the rejected claim 16.
With respect to claim 19, which further limits claim 18, EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis teaches wherein said at least one global lesions image comprise at least one image of the underside body surface of said companion animal (Fig.2).
With respect to claim 20, which further limits claim 18, EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis teaches wherein said companion animal data further comprise at least one lesion specific image of a cutaneous lesion of said companion animal (Fig.2).
Claims 4 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis, Frosch’933 (US 2021/0158933) and further in view of Negishi’912 (US 2006/0229912).
With respect to claim 4, which further limits claim 3, the combination of EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis and Frosch’933 does not teach wherein said at least one lesion specific image comprises at least an enlarged image of at least one area of interest including said at least one cutaneous lesion.
Negishi’912 teaches wherein said at least one lesion specific image comprises at least an enlarged image of at least one area of interest including said at least one cutaneous lesion (abstract).
Therefore, 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 the combination of EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis and Frosch’933 according to the teaching of Negishi’912 to enlarge the cropped skin image because this will allow the diseases of the skin to be analyzed more effectively.
With respect to claim 11, which further limits claim 1, EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis teaches wherein an additional lesion image is used,
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis, Frosch’933 (US 2021/0158933) and further in view of Kimura’089 (US 10,682,089).
With respect to claim 12, which further limits claim 1, EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis and Frosch’933 does not teach comprising the step of providing to a user interface said score relative to said companion animal and generated at step b).
Kimura’089 teaches comprising the step of providing to a user interface said score relative to said companion animal and generated at step b) (Fig.5).
Therefore, 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 EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis and Frosch’933 according to the teaching of Kimura’089 to include a user interface to display the severity scores for the skin image because this will allow the severity scores for the skin image to be provided to a user more effectively.
Contact
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HUO LONG CHEN whose telephone number is (571)270-3759. The examiner can normally be reached on M-F 9am - 5pm. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Tieu, Benny can be reached on (571) 272-7490. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/HUO LONG CHEN/Primary Examiner, Art Unit 2682