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 .
Priority
The instant application claims benefit to provisional application No. 63/276,694 filed on 11/08/2021. Domestic benefit is acknowledged. Thus, the effective filing date of Claims 1-42 is 11/08/2021.
Information Disclosure Statement
The information disclosure statement (“IDS”) filed on 05/07/2024 was reviewed and the listed references were noted.
Drawings
The 9 page drawings have been considered and placed on record in the file.
Status of Claims
Claims 1-3, 5, 8-10, 16, 18, 20, 24-25, 28-31, 33, 35-36, and 42 are currently pending. Claims 4, 6-7, 11-15, 17, 19, 21-23; 26-27; 32, 34, and 37-41 are canceled.
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, 3, 5, 8, 28-30, 36, and 42 are rejected under 35 U.S.C. 102 (a)(1) as being anticipated by Zingaretti et. al. (US 20180214072).
Consider Claim 1, Zingaretti teaches “A system for performing a remote hair analysis of the head of a hair restoration candidate, comprising: a) one or more image-capturing devices adapted to connect directly, or through a computer, to the internet, for capturing images or video segments of the head of said hair restoration candidate to be processed,” (Zingaretti; [0062]; “Having created the patient's record, the physician may utilize the mobile microscope camera attached to the mobile device, along with associated software application, to capture a still image of one or more predetermined areas of the patient's scalp, and optionally store the image(s) in an image repository, or image library on the mobile device.”) “and for transmitting the captured images or video segments to one or more computing devices;” (Zingaretti; [0067]; “As indicated earlier, this repository may reside on the mobile device itself, or at another location, for example on portable data storage devices (for example, a USB drive), a local computer hard drive to which the mobile device is typically synchronized, or to a remote media-sharing environment, such as the Cloud, to which the device can connect via the internet.”) “and b) one or more central computing devices, configured with suitable hardware for running an operating software,” (Zingaretti; [0011]; “The software/program for executing instructions for determining hair metric (or any other methodology of the present disclosure) may be used in conjunction with a mobile device (e.g., smart phone), tablet, iPad, laptop, personal computer or other processing unit.”) “which is configured to receive images or video segments of hair restoration candidates' heads, and to process and analyze perceptible hair parameters” (Zingaretti; Fig. 5 (See figure below)) “therein for inferring as to the candidates' eligibility for a hair restoration procedure.” (Zingaretti; [0038]; “The present disclosure provides comprehensive systems and methods for managing hair loss, enabling the individual experiencing hair loss and/or the physician consulting the patient to manage the hair loss process over a period of time, based upon one or more characteristics or parameters of the individual's hair loss, …. Management may comprise, but is not limited to, … or recommending/performing hair transplantation procedure.”).
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Consider Claim 3, Zingaretti teaches “A system according to claim 1, wherein the one or more image capturing devices are adapted to perform a partial or complete analysis of the captured images or video segments” (Zingaretti; [0062]; “Having created the patient's record, the physician may utilize the mobile microscope camera attached to the mobile device, along with associated software application, to capture a still image of one or more predetermined areas of the patient's scalp…”) “and wherein the images or video segments are captured by manually moving the image-capturing devices by the candidate or by another assisting person.” (Zingaretti; [0062]; “Having created the patient's record, the physician may utilize the mobile microscope camera attached to the mobile device, along with associated software application, to capture a still image of one or more predetermined areas of the patient's scalp, and optionally store the image(s) in an image repository, or image library on the mobile device.”; Examiner notes examiner has interpreted images captured in Zingaretti are captured and manually positioned by the physician.).
Consider Claim 5, Zingaretti teaches “A system according to claim 1, wherein the image-capturing device is selected from the group of: a smartphone; a tablet; a digital camera; and Light Detection and Ranging (LIDAR) sensors.” (Zingaretti; [0062]; “Having created the patient's record, the physician may utilize the mobile microscope camera attached to the mobile device, along with associated software application, to capture a still image of one or more predetermined areas of the patient's scalp…”).
Consider Claim 8, Zingaretti teaches “A method for performing a remote hair analysis of the head of a hair restoration candidate, comprising: a) one or more image-capturing devices adapted to connect directly, or through a computer, to the internet, for capturing images or video segments of the head of said hair restoration candidate to be processed,” (Zingaretti; [0062]; “Having created the patient's record, the physician may utilize the mobile microscope camera attached to the mobile device, along with associated software application, to capture a still image of one or more predetermined areas of the patient's scalp, and optionally store the image(s) in an image repository, or image library on the mobile device.”) “b) transmitting the captured images or video segments to one or more central computing devices;” (Zingaretti; [0067]; “As indicated earlier, this repository may reside on the mobile device itself, or at another location, for example on portable data storage devices (for example, a USB drive), a local computer hard drive to which the mobile device is typically synchronized, or to a remote media-sharing environment, such as the Cloud, to which the device can connect via the internet.”) “c) receiving images or video segments of hair restoration candidates' heads; and” (Zingaretti; Fig. 5 (See figure above)) “d) processing and analyzing perceptible hair parameters, for inferring as to the candidates' eligibility for a hair restoration procedure.” (Zingaretti; [0038]; “The present disclosure provides comprehensive systems and methods for managing hair loss, enabling the individual experiencing hair loss and/or the physician consulting the patient to manage the hair loss process over a period of time, based upon one or more characteristics or parameters of the individual's hair loss, …. Management may comprise, but is not limited to, … or recommending/performing hair transplantation procedure.”).
Consider Claim 28, Zingaretti teaches “A system for performing a remote hair analysis of the head of a hair restoration candidate, comprising: a) one or more image-capturing devices adapted to connect directly, or through a computer, to the internet, for capturing images or video segments of the head of said hair restoration candidate to be processed,” (Zingaretti; [0062]; “Having created the patient's record, the physician may utilize the mobile microscope camera attached to the mobile device, along with associated software application, to capture a still image of one or more predetermined areas of the patient's scalp, and optionally store the image(s) in an image repository, or image library on the mobile device.”) “and for transmitting the captured images or video segments to one or more computing devices;” (Zingaretti; [0067]; “As indicated earlier, this repository may reside on the mobile device itself, or at another location, for example on portable data storage devices (for example, a USB drive), a local computer hard drive to which the mobile device is typically synchronized, or to a remote media-sharing environment, such as the Cloud, to which the device can connect via the internet.”) “and b) one or more central computing devices, configured with suitable hardware for running an operating software,” (Zingaretti; [0011]; “The software/program for executing instructions for determining hair metric (or any other methodology of the present disclosure) may be used in conjunction with a mobile device (e.g., smart phone), tablet, iPad, laptop, personal computer or other processing unit.”) “which is configured to receive images or video segments of hair restoration candidates' heads, and to process and analyze perceptible hair parameters” (Zingaretti; Fig. 5 (See figure above)) “therein for inferring as to the candidates' eligibility for a hair restoration procedure.” (Zingaretti; [0038]; “The present disclosure provides comprehensive systems and methods for managing hair loss, enabling the individual experiencing hair loss and/or the physician consulting the patient to manage the hair loss process over a period of time, based upon one or more characteristics or parameters of the individual's hair loss, …. Management may comprise, but is not limited to, … or recommending/performing hair transplantation procedure.”).
Consider Claim 29, Zingaretti teaches “A system according to claim 28, wherein the image-capturing device is selected from the group of: a smartphone; a tablet; a digital camera; and Light Detection and Ranging (LIDAR) sensors.” (Zingaretti; [0062]; “Having created the patient's record, the physician may utilize the mobile microscope camera attached to the mobile device, along with associated software application, to capture a still image of one or more predetermined areas of the patient's scalp…”).
Consider Claim 30, Zingaretti teaches “A system according to claim 28, wherein the candidate's head is shaved or unshaved head.” (Zingaretti; Fig 2a (See image below), Examiner notes the candidate’s head in the captured image is interpreted to be an unshaved head.).
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Consider Claim 36, Zingaretti teaches “A system according to claim 28, wherein a calibration method is attaching a marked layout with known distances on the head at the time of taking the pictures, or is used to determine the equivalent value of each pixel in the image.” (Zingaretti; [0062]; “The physician or other user may utilize some method of ensuring that the same area(s) is/are imaged. For example, one may utilize fiducials, such as physical markers or anatomical landmarks on a patient's skin or body surface, e.g., a follicular unit or hair, a mole, a scar, a freckle, a wrinkle, a bump, or a depression of the body surface, as previously discussed. The fiducials may also be objects permanently or temporarily placed on or affixed to the patient's skin, such a tattoo. As indicated previously, a fiducial is an object in a field of view of an imaging device that acts as a reference, and may comprise the above or any combination thereof.”).
Consider Claim 42, Zingaretti teaches “A system according to claim 28, wherein a magnification device is used in conjunction with the capturing device, in order to improve the resolution and clarity.” (Zingaretti; [0060]; “the physician may utilize a computer screen, mobile device, tablet, smartphone or other visual display to which an image acquisition device (for example, a digital camera incorporated into a mobile telephone, a microscopic lens, such as a ProScope mobile microscope camera from Bodelin Technologies, or other such microscopic lens or camera) can be attached.”, Examiner notes it would be obvious to a person in the art to use a microscope lens with a capturing device to capture more clear images of hair follicles.).
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
Determining the scope and contents of the prior art.
Ascertaining the differences between the prior art and the claims at issue.
Resolving the level of ordinary skill in the pertinent art.
Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim 35 is rejected under 35 U.S.C. 103 as being unpatentable over Zingaretti et. al. (US 20180214072) in view of Punyani et. al. (US 20220335614 A1, effectively filed on 04/14/2021).
Consider Claim 35, Zingaretti teaches “A system according to claim 28, wherein a total coverage in unshaved head” (Zingaretti; Fig 2a (See image above), Examiner notes the candidate’s head in the captured image is interpreted to be an unshaved head.) “is calculated based on: identifying the portion of the image that belongs to the head,” (Zingaretti; Fig 2a (See image above)) “(Zingaretti; [0016]; “In further embodiments, the method may comprise determining a density in the potential recipient area and automatically proposing that a hair transplantation be considered at present or during certain proposed time frame if the hair density is less than a predetermined number of hair follicles or follicular units per unit area.”; Examiner notes Zingaretti teaches a predetermined number of hair follicles is based on “the typical number of hair, for a healthy head of hair, with respect to a patient who has had no hair enhancement treatments.” (Zingaretti; [0050])). Accordingly, before the effective filing date of the instant application, it would have been obvious to one of ordinary skill in the art to combine the embodiments of Zingaretti with each other to further determine the density of hair in an image. One of ordinary skill in the art would be motivated to combine the embodiments of Zingaretti with each other to use the detected density and coverage of hair on a candidate to determine if there is enough hair loss to be eligible for hair restoration. Accordingly, the combination of embodiments of Zingaretti discloses the limitations of Claim 2 described above.
Zingaretti does not explicitly disclose “is calculated based on: identifying the portion of the image that belongs to the head, classifying pixels that belong to the scalp versus the hair”. However, in analogous field of endeavor, Punyani teaches “is calculated based on: identifying the portion of the image that belongs to the head, classifying pixels that belong to the scalp versus the hair” (Punyani; [0054]; “For example, pixel data 202ap further includes pixels representative of features of scalp skin or hair follicle regions corresponding to various image classifications…”). Accordingly, before the effective filing date of the instant application, it would have been obvious to one of ordinary skill in the art to combine Zingaretti with the teachings of Punyani to further use pixel analysis of the capture images to detect hair and skin on a candidate’s head. One of ordinary skill in the art would be motivated to combine Zingaretti and Punyani to use pixel analysis to more accurately detect the amount of hair is present on a candidate’s head. Accordingly, the combination of Zingaretti and Punyani discloses the invention of Claim 2.
Allowable Subject Matter
10. Claims 2, 9-10, 16, 18, 20, 24-25, 31 and 33 are objected to as being dependent upon a rejected base claim, but could be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. The following is a statement of reasons for the indication of allowable subject matter:
Consider Claim 2, none of the cited prior art references, alone or in combination, provides a motivation to teach the ordered combination of the limitations recited in Claim 2 with the limitations of the claims it depends from.
Consider Claim 9, Zingaretti teaches “(Zingaretti; Fig 2a, Examiner notes the candidate’s head in the captured image is interpreted to be an unshaved head.) “
In another analogous field of endeavor, Punyani teaches “A method according to claim 8, wherein the analysis comprises one of the following operations: - classification of pixels as related to hair within a received image, or a single frame of a head scan video of the candidates head,” (Punyani; Abstract; “A digital image of a user is received at an imaging application (app) and comprises pixel data of at least a portion of a scalp region of the user's scalp….analyzes the image to determine at least one image classification of the user's scalp region.”) “performed by: a) receiving an input image frame of a shaved head as R,G,B pixels;” (Punyani; [0047]; Each of these images may comprise pixel data (e.g., RGB data) comprising feature data and corresponding to scalp regions of respective users, within the respective image.”) “ (Punyani; [0055]; “A digital image, such as a training image, an image as submitted by users, or otherwise a digital image (e.g., any of images 202a, 202b, and/or 202c), may be or may comprise a cropped image…. Cropped portion 202ac1 represents a first cropped portion of image 202a that removes portions of the user's scalp (outside of cropped portion 202ac1) that may not include readily identifiable scalp skin or hair follicle region features.” (Emphasis added)) “and classifying pixels that can be associated with a cropped human head.” (Punyani; [0056]; “It is to be understood that the disclosure for image 202a of FIG. 2 applies the same or similarly for other digital images described herein, including, for example, images 202b and 202c, where such images also comprise pixels that may be analyzed and/or used for training of model(s) as described herein.”) “receiving frames of video segments of a cropped head;” (Punyani; [0068]; In some embodiments an image may comprise or refer to a plurality of images such as a plurality of images (e.g., frames) as collected using a digital video camera. Frames comprise consecutive images defining motion, and can comprise a movie, a video, or the like.”) “ related to the scalp;” (Punyani; [0053]; “In example image 202a, each of pixel 202ap1, pixel 202ap2, and pixel 202ap3 are each representative of features of scalp skin or hair follicle regions corresponding to image classifications of a scalp region.”) “and classifying pixels as related to hair or said scalp;” (Punyani; [0054]; “For example, pixel data 202ap further includes pixels representative of features of scalp skin or hair follicle regions corresponding to various image classifications,…”) “
In another analogous field of endeavor, Rahman et. al. (“Context based algorithmic framework for identifying and classifying embedded images of follicle units” published on 03/21/2014) teaches “(Rahman; 4.3.1 Detect Follicles pixel group by merging; “We can start scanning the image from left to right and search for any dark region which is a possible follicle….it first detects a possible dark follicle pixel.”) “the identification of individual hair follicles formed by groups of residing pixels identified as hair by:” (Rahman; 4.3.1 Detect Follicles pixel group by merging; “Whenever we get a dark pixel there are two possibilities. Either this pixel is an instance of a newly detected follicle or it is the continuation of a previously detected follicle. To confirm about this we can check four surrounding pixels. The algorithm checks the points (9,1),(8,1),(7,1) and (7,2) for the tail of any previously detected follicle. For each follicle unit detected we record the start point or head pixel and endpoint or tail pixel co-ordinates. If continuation found then we update the endpoint or tail with current pixel coordinates of the already detected follicle unit.”) “(Rahman; 4.3.1 Detect Follicles pixel group by merging; “Whenever we get a dark pixel there are two possibilities. Either this pixel is an instance of a newly detected follicle or it is the continuation of a previously detected follicle. To confirm about this we can check four surrounding pixels. The algorithm checks the points (9,1),(8,1),(7,1) and (7,2) for the tail of any previously detected follicle. For each follicle unit detected we record the start point or head pixel and endpoint or tail pixel co-ordinates. If continuation found then we update the endpoint or tail with current pixel coordinates of the already detected follicle unit.”) “the generation of a profile of each identified hair follicle by” (Rahman; Fig. 2 (See figure below); Examiner notes Rahman teaches that each hair follicle is analyzed for its location and number of hair per follicle, and examiner has interpreted each follicle group as a profile.) “: (Rahman; Fig. 2 (See figure below); Examiner notes the position of each follicle from its neighbor is interpreted to be the orientation of each follicle.) “(Rahman; 4.3.1 Detect Follicles pixel group by merging; “We can start scanning the image from left to right and search for any dark region which is a possible follicle….it first detects a possible dark follicle pixel.”).
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In another analogous field of endeavor, Huang; (WO 2022134703 filed 09/26/2021) teaches “…determining a threshold for classifying pixels having a score below said threshold as related to scalp and pixels having a score above said threshold as related to hair;” (Huang; Fig. 8 (See image below); Pg. 8, Para. 8; “By way of example only, in a global binarization method, a first image portion may for example be gray-scaled, converted into a grayscale image, and then pixels with a grayscale greater than a preset threshold are set to black , and set the pixels whose gray level is less than the preset threshold as white, and invert the obtained image to obtain the corresponding binarized image.”; Examiner notes pixels set to black is interpreted to be detected hair and pixels set to white is interpreted to be detected skin based on Fig. 8.).
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None of the cited prior art references, alone or in combination, provides a motivation to teach the claim limitations: “receiving each Hair follicle represented by a predetermined number of pixels”, “receiving video segments of a shaved head; and identifying and characterizing the hair follicles on each scanned segment of said shaved head”, “calculating the estimated hair coverage by: receiving frames of video segments and cropping the head from each frame by: creating a Semantic Segmentation Mask; creating a Grabcuts Mask; joining said masks to create a final cropping mask; removing imperfections from said final cropping mask using morphological closing and opening; classifying each pixel as scalp or hair by: creating a Color Neighboring Classification; creating a Luminosity and Saturation Classification; combining said classifications into a final score”, and “calculating the final hair coverage percentage by: applying said threshold on the final score image and calculating the percentage of the above-threshold score pixels being related to hair, with respect to the below-score pixels being related to skin; counting the number of pixels classified as hair and dividing the counted number by the total number of pixels in the cropped image.”, recited in Claim 9 with the limitations of the claims it depends from.
Consider Claims 10, 16, 18, 20 and 24-25, none of the cited prior art references, alone or in combination, provides a motivation to teach the ordered combination of the limitations recited in Claims 10, 16, 18, 20 and 24-25 with the limitations of the claims it depends from.
Consider Claim 31, Zingaretti teaches “A system according to claim 28, wherein the one or more central computing devices are configured to: receive and analyze images a candidate's head,” (Zingaretti; Fig. 5 (See figure above); Step 505) “and to identify one or more follicles,” (Zingaretti; Fig. 2e (See image below); Element 300; [0072]; “It can be seen that the toggle switch 298 corresponding to the highlighting of F1 type follicular units has been selected, which instructs the software to highlight the F1 type follicular units 300 to the user, for example, by changing their color to blue perhaps.”) “and for each, one or more property like angle or number of hair;” (Zingaretti; Fig, 2c (See image below); Density Image, Number of Hairs)
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Consider Claim 33, none of the cited prior art references, alone or in combination, provides a motivation to teach the ordered combination of the limitations recited in Claim 33 with the limitations of the claims it depends from.
Conclusion
11. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Annie Pham whose telephone number is (571)272-1673. The examiner can be normally be reached Mon-Fri 9:00a – 5:00p.
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/ANNIE H PHAM/Examiner, Art Unit 2662
/Siamak Harandi/Primary Examiner, Art Unit 2662
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