DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Objections
2. Claim 1 objected to because of the following informalities: The limitation “the surface of the scalp” on line 1 is not properly established or recited prior to this limitation, despite stating “the” in this limitation. Examiner suggests rewriting this limitation to read “a surface of a scalp”. Appropriate correction is required.
Claim 1 objected to because of the following informalities: The limitation “the Measurement of Bald Areas” on lines 1-2 is not properly established properly established or recited prior to this limitation, despite stating “the” in this limitation. Examiner suggests rewriting this limitation to read “a Measurement of Bald Areas”. Appropriate correction is required.
Claim 1 objected to because of the following informalities: The limitation “the counting of micropolygons” on line 3 is not properly established or recited prior to this limitation, despite stating “the” in this limitation. Examiner suggests rewriting this limitation to read “a counting of micropolygons”. Appropriate correction is required.
Claim 1 objected to because of the following informalities: The limitation “the use of technologies” on line 5 is not properly established or recited prior to this limitation, despite stating “the” in this limitation. Examiner suggests rewriting this limitation to read “a use of technologies”. Appropriate correction is required.
Claim 1 objected to because of the following informalities: The limitation “the area of interest” on line 7 is not properly established or recited prior to this limitation, despite stating “the” in this limitation. Examiner suggests rewriting this limitation to read “an area of interest”. Appropriate correction is required.
Claim 1 objected to because of the following informalities: The limitation “the electronic device” on lines 7-8 is not properly established or recited prior to this limitation, despite stating “the” in this limitation. Examiner suggests rewriting this limitation to read “an electronic device”. Appropriate correction is required.
Claim 1 objected to because of the following informalities: The limitation “the cumulative sum” on line 13 is not properly established or recited prior to this limitation, despite stating “the” in this limitation. Examiner suggests rewriting this limitation to read “a cumulative sum”. Appropriate correction is required.
Claim 2 objected to because of the following informalities: The limitation “the use of TrueDepth” on line 3 is not properly established or recited prior to this limitation, despite stating “the” in this limitation. Examiner suggests rewriting this limitation to read “a use of TrueDepth”. Appropriate correction is required.
Claim 2 objected to because of the following informalities: The limitation “the measurement of the surface of 3D models” on line 6 is not properly established or recited prior to this limitation, despite stating “the” in this limitation. Examiner suggests rewriting this limitation to read “a measurement of a surface of 3D models”. Appropriate correction is required.
Claim 3 objected to because of the following informalities: The limitation “the use of technologies” on line 3 is not properly established or recited prior to this limitation, despite stating “the” in this limitation. Examiner suggests rewriting this limitation to read “a use of technologies”. Appropriate correction is required.
Claim 3 objected to because of the following informalities: The limitation “the foundation for rendering the 3D model of the patient’s scalp” on lines 3 is not properly established or recited prior to this limitation, despite stating “the” in this limitation. Examiner suggests rewriting this limitation to read “a foundation for rendering a 3D model of a patient’s scalp”. Appropriate correction is required.
Claim 4 objected to because of the following informalities: The limitation “the electronic device” on line 6 is not properly established or recited prior to this limitation or in any of the claims this claim is dependent on, despite stating “the” in this limitation. Examiner suggests rewriting this limitation to read “an electronic device”. Appropriate correction is required.
Claim 4 objected to because of the following informalities: The limitation “the 3D Point Cloud” on line 9 is not properly established or recited prior to this limitation or in any of the claims this claim is dependent on, despite stating “the” in this limitation. Examiner suggests rewriting this limitation to read “a 3D Point Cloud”. Appropriate correction is required.
Claim 4 objected to because of the following informalities: The limitation “the operator, through the application” on lines 10-11 is not properly established or recited prior to this limitation or in any of the claims this claim is dependent on, despite stating “the” in this limitation. Examiner suggests rewriting this limitation to read “an operator, through an application”. Appropriate correction is required.
Claim 4 objected to because of the following informalities: The limitation “3D models and/or 3D meshes” on lines 14-15 are unclear on whether it refers to the “3D models and/or 3D meshes” previously defined in claim 2, or whether it refers to a new set of 3D models and/or 3D meshes. Examiner suggests rewriting the limitation to read “The 3D models and/or 3D meshes”. Appropriate correction is required.
Claim 5 objected to because of the following informalities: The limitation “the mapping, processing, and image reconstruction application/software for specialized 3D measurement” on lines 7-8 is not properly established or recited prior to this limitation or in any of the claims this claim is dependent on, despite stating “the” in this limitation. Examiner suggests rewriting the limitation to read “a mapping, processing, and image reconstruction application/software for specialized 3D measurement”. Appropriate correction is required.
Claim 15 objected to because of the following informalities: The limitation “the counting of micropolygons” on lines 2-3 is not properly established or recited prior to this limitation, despite stating “the” in this limitation. Examiner suggests rewriting this limitation to read “a counting of micropolygons”. Appropriate correction is required.
Claim 16 objected to because of the following informalities: The limitation “the counting of micropolygons” on line 3 is not properly established or recited prior to this limitation, despite stating “the” in this limitation. Examiner suggests rewriting this limitation to read “a counting of micropolygons”. Appropriate correction is required.
3. Applicant is advised that should claim 9 be found allowable, claim 10 will be objected to under 37 CFR 1.75 as being a substantial duplicate thereof. When two claims in an application are duplicates or else are so close in content that they both cover the same thing, despite a slight difference in wording, it is proper after allowing one claim to object to the other as being a substantial duplicate of the allowed claim. See MPEP § 608.01(m).
Claim Rejections - 35 USC § 101
4. 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.
5. Claim 16 rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim does not fall within at least one of the four categories of patent eligible subject matter because the claimed invention is software per se and merely refers to a "Computer Program", and does not have a physical or tangible form as is claimed without any structural recitations.
As the courts' definitions of machines, manufactures and compositions of matter indicate, a product must have a physical or tangible form in order to fall within one of these statutory categories. Digitech, 758 F.3d at 1348, 111 USPQ2d at 1719. Thus, the Federal Circuit has held that a product claim to an intangible collection of information, even if created by human effort, does not fall within any statutory category. Digitech, 758 F.3d at 1350, 111 USPQ2d at 1720 (claimed “device profile” comprising two sets of data did not meet any of the categories because it was neither a process nor a tangible product). Similarly, software expressed as code or a set of instructions detached from any medium is an idea without physical embodiment. See Microsoft Corp. v. AT&T Corp., 550 U.S. 437, 449, 82 USPQ2d 1400, 1407 (2007); see also Benson, 409 U.S. 67, 175 USPQ2d 675 (An "idea" is not patent eligible). Thus, a product claim to a software program that does not also contain at least one structural limitation (such as a “means plus function” limitation) has no physical or tangible form, and thus does not fall within any statutory category.
Claim Rejections - 35 USC § 112
6. The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
7. The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
8. Claims 1, 4 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as 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.
Claim 1 recites the limitation "the selected region" in line 10. There is insufficient antecedent basis for this limitation in the claim. The limitation is not defined previously in the claim, and it is additionally unclear whether “the selected region” is referring to “the area of interest” defined previously in claim 1, or if it is referring to a newly defined “selected region”. For the purposes of examination, this limitation will be interpreted as “the area of interest”.
Claim 1 recites the limitation "the demarcated area" in line 11. There is insufficient antecedent basis for this limitation in the claim. The limitation is not defined previously in the claim, and it is additionally unclear whether “the demarcated area” is referring to “the area of interest” defined previously in claim 1, or if it is referring to a newly defined “demarcated area”. For the purposes of examination, this limitation will be interpreted as “the area of interest”.
Claim 1 recites the limitation "the area" in line 12. There is insufficient antecedent basis for this limitation in the claim. The limitation is not defined previously in the claim, and it is additionally unclear whether “the area” is referring to “the area of interest” defined previously in claim 1, the “area” of the micropolygons, the “area” of the 3D model, or if it is referring to a newly defined “area”. For the purposes of examination, this limitation will be interpreted as “the total area of the area of interest”.
Claim 1 recites the limitation "the total area" in line 14. There is insufficient antecedent basis for this limitation in the claim. The limitation is not defined previously in the claim, and it is additionally unclear whether “the total area” is referring to “the area of interest” defined previously in claim 1, the “total area” of the micropolygons, the “total area” of the 3D model, or if it is referring to a newly defined “total area”. For the purposes of examination, this limitation will be interpreted as “the total area of the area of interest”.
Claim 1 recites the limitation "the selected area" in line 14. There is insufficient antecedent basis for this limitation in the claim. The limitation is not defined previously in the claim, and it is additionally unclear whether “the selected area” is referring to “the area of interest” defined previously in claim 1, or if it is referring to a newly defined “selected area”. For the purposes of examination, this limitation will be interpreted as “the area of interest”.
Claim 4 recites the limitation "the area" in line 14. There is insufficient antecedent basis for this limitation in the claim. The limitation is not defined previously in the claim or in any claims this claim is dependent on, and it is additionally unclear whether “the area” is referring to “bald areas”, “areas with thinned hair”, “areas with thick hair”, or to the area of the “3D models and/or 3D meshes” defined previously in claim 2, or if it is referring to a newly defined “area”. For the purposes of examination, this limitation will be interpreted as “an area the 3D models and/or 3D meshes”.
Claim Rejections - 35 USC § 103
9. 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.
10. 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.
11. Claims 1, 15 is rejected under 35 U.S.C. 103 as being unpatentable over Zhang (US 9743993 B2), hereinafter Zhang, in view of Gu (CN112184798A), hereinafter Gu.
Regarding claim 1, Zhang teaches a method for Measuring the Surface of the Scalp for the Measurement of Bald Areas (recipient areas), Areas with Thinned Hair, Areas with Thick Hair (donor areas) (Fig. 1, Col. 10 line 55 – Col. 11 line 6, wherein proposed hair elements or a person’s scalp are processed, which is defined as elements where follicular units are harvested and implanted to, which is interpreted as recipient areas and donor areas, and wherein proposing a boundary curve for the proposed hair elements is interpreted as measuring the areas of a scalp), in 3D models and/or 3D meshes created by technologies that generate life-size 3D models (Col. 12, lines 47-54, wherein a 3D model of a person's scalp can be generated using a 3D laser scanner, and/or stitching digital images together, which is interpreted as technologies that generate life-size 3D models), the method comprising: Receive the 3D model and/or mesh through the use of technologies equipped with mechanisms for capturing three-dimensional information (Col. 12, lines 47-54, wherein a 3D model of a person's scalp can be generated using a 3D laser scanner, and/or stitching digital images together, which is interpreted as technologies for capturing three dimensional information); and Delimit the area of interest through an interactive interface on the electronic device, directly on the virtual surface of the 3D model or 3D mesh, using any interactive interface designed to capture multiple input modalities (Col. 11, lines 3-28, wherein proposed hair elements, including areas of hair to be harvested from, interpreted as donor areas, and areas of hair to be transplanted to, interpreted as recipient areas, may be selected by user input drawing, and wherein user modifications in a 2D view is converted to corresponding 3D modifications of a 3D mesh model, which is interpreted as delimiting areas of interest of hair through an interactive interface directly on the surface of a 3D model/mesh, wherein the user input may be from multiple different devices and sources, which is interpreted as the interface capturing multiple input modalities).
Zhang does not teach the counting of micropolygons in 3D models and/or 3D meshes, processing the micropolygons within the selected region, identifying the micropolygons that are fully or partially included in the demarcated area; and count the micropolygons to measure the area, determining the total area through the cumulative sum of the individual areas of the micropolygons that make up the selected region.
Gu teaches the counting of micropolygons in 3D models and/or 3D meshes, processing the micropolygons within the selected region, identifying the micropolygons that are fully or partially included in the demarcated area (Paragraph 56, wherein a polygon demarcating a surface area on a 3D model is selected interactively by a user; Paragraph 80-82, wherein generating a set of small triangles within the polygon is interpreted as processing the micropolygons within the selected region, the set of small triangles is interpreted as micropolygons, and wherein removing triangles whose centroids are outside the polygon from the set is interpreted as identifying micropolygons that are fully or partially included in the area); and counting the micropolygons to measure the area, determining the total area through the cumulative sum of the individual areas of the micropolygons that make up the selected region (paragraph 85-86, wherein calculating and summing up the area of each small triangle to determine the area of the selected polygon is interpreted as counting and determining the total area through the cumulative sum of the areas of the micropolygon that make up the selected region).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Zhang with the teachings of Gu for this method of mapping areas of a scalp surface. Zhang teaches a method of determining and modelling the bald areas and areas with hair of a person’s scalp, and allowing a user to demarcate areas as being donor areas or recipient areas for hair transplants. While Gu does not discuss modelling a person’s scalp, or about hair transplants, it does teach a method of determining the surface area of a user inputted area of a 3D model via counting and measuring the area of micropolygons. Gu describes a method of easily determining the surface area of an area determined by a user in order to improve both accuracy and speed of that process. As Zhang describes determining areas of a 3D model of a person’s scalp, and allowing users to demarcate areas of that person’s scalp, it would be obvious to combine these references as Zhang would appreciate the more efficient way of calculating those demarcated areas described in Gu.
Regarding claim 15, Zhang teaches a Scalp Surface Measurement System for Measuring Bald Areas (recipient areas), Areas with Thinned Hair, Areas with Thick Hair (donor areas) (Fig. 1, Col. 10 line 55 – Col. 11 line 6, wherein proposed hair elements or a person’s scalp are processed, which is defined as elements where follicular units are harvested and implanted to, which is interpreted as recipient areas and donor areas, and wherein proposing a boundary curve for the proposed hair elements is interpreted as measuring the areas of a scalp), comprising a camera hardware equipped with at least one three-dimensional information capture technology, an electronic device, and a measurement application or software installed on the electronic device (Col. 12, lines 47-54, wherein a 3D model of a person's scalp can be generated using a 3D laser scanner, and/or stitching digital images together, which is interpreted as three-dimensional information capture technology, and capturing a 3D model of a person’s scalp suggests it is additionally a measurement application).
Zhang does not teach the counting of micropolygons in 3D models and/or 3D meshes.
Gu teaches the counting of micropolygons in 3D models and/or 3D meshes (paragraph 85-86, wherein calculating and summing up the area of each small triangle to determine the area of the selected polygon is interpreted as counting the micropolygons of a selected polygon, wherein the selected polygon is defined as a region of a 3D model).
The motivation to combine would be the same as that set forth for claim 1.
12. Claims 2-3 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang (US 9743993 B2), hereinafter Zhang.
Regarding claim 2, Zhang teaches a method for Scalp Surface Mapping to Measure Bald Areas (recipient areas), Areas with Thinned Hair, Areas with Thick Hair (donor areas) (Fig. 1, Col. 10 line 55 – Col. 11 line 6, wherein proposed hair elements or a person’s scalp are processed, which is defined as elements where follicular units are harvested and implanted to, which is interpreted as recipient areas and donor areas, and wherein proposing a boundary curve for the proposed hair elements is interpreted as measuring the areas of a scalp), characterized by the use of TrueDepth, Structured Light, LiDAR, Time-of-Flight (ToF) Sensors, Photogrammetry, Stereoscopic Vision, and similar technologies (Col. 12, lines 47-54, wherein a 3D model of a person's scalp can be generated using a 3D laser scanner, which is interpreted as using LiDAR, and/or stitching digital images together, which is interpreted as similar in technology to the listed techniques), for measuring bald areas (recipient areas), areas with thinned hair, areas with thick hair (donor areas), through the measurement of the surface of 3D models and/or 3D meshes created by these technologies or other similar technologies that generate life-size 3D models (Col. 12, lines 47-54, wherein a 3D model of a person's scalp can be generated using a 3D laser scanner, and/or stitching digital images together, which is interpreted as technologies that generate life-size 3D models).
The claimed subject matter would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention given the teachings of Zhang. Zhang clearly teaches a method of determining the bald areas and areas with hair of a person’s scalp. Zhang further describes methods of obtaining a 3D model of a person’s scalp, using multiple techniques such as 3D laser scanning, or determining a model via a plurality of images taken of a person’s scalp. It would be obvious that the teachings of Zhang for this method of determining bald areas and hair areas of a person’s scalp, as well as the boundaries of said areas, for the purposes of demarcating areas for hair transplants, would involve determining the surface area of each element. Zhang further discusses generating a 3D model of a person’s scalp, and having that data be generated based off of data taken from a 3D mesh of a person’s scalp. Because of this, the claimed subject matter would have been obvious to one of ordinary skill in the art given the teachings of Zhang.
Regarding claim 3, Zhang teaches a method for Scalp Surface Mapping to Measure Bald Areas (recipient areas), Areas with Thinned Hair, Areas with Thick Hair (donor areas) (Fig. 1, Col. 10 line 55 – Col. 11 line 6, wherein proposed hair elements or a person’s scalp are processed, which is defined as elements where follicular units are harvested and implanted to, which is interpreted as recipient areas and donor areas, and wherein proposing a boundary curve for the proposed hair elements is interpreted as measuring the areas of a scalp), characterized by the use of technologies equipped with mechanisms for capturing three-dimensional information (Col. 12, lines 47-54, wherein a 3D model of a person's scalp can be generated using a 3D laser scanner, and/or stitching digital images together, which is interpreted as the use of technologies for capturing three-dimensional information), which will be used to generate a 3D mesh (“3D MESH”), serving as the foundation for rendering the 3D model of the patient’s scalp for the mapping and measurement of bald areas (recipient areas), areas with thinned hair, areas with thick hair (donor areas) (Col. 11 lines 24-28, wherein 3D modifications to a scalp are based on 3D data obtained from a 3D mesh model, which is interpreted as the 3D mesh serving as a foundation for rendering a 3D model of the patient’s scalp; Fig. 4-5, wherein a patient’s scalp, recipient areas, and donor areas can be generated and rendered as a 3D model).
The motivation would be the same as that for claim 2.
13. Claims 4- 14, 16 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang in view of Gu as applied to claim 2 above, and further in view of Katekari (US 20220343493 A1), hereinafter Katekari.
Regarding claim 4, Zhang in view of Gu disclose the method of claim 1. Additionally, Zhang teaches the method according to claim 2, characterized by the method comprising: Generate the 3D Mesh ("3D MESH") by marking points, by the operator, through the application, delimiting, painting, and automatically recording the scalp region (Col. 11, lines 3-28, wherein proposed hair elements, including areas of hair to be harvested from, interpreted as donor areas, and areas of hair to be transplanted to, interpreted as recipient areas, may be selected by user input freehand, which is interpreted as the operator through an application delimiting and painting the scalp region, and wherein user modifications in a 2D view is converted to corresponding 3D modifications of a 3D mesh model, which is interpreted recording the delimiting of the scalp region onto a 3D mesh model), generating a more detailed mesh model of the head, created based on data from the technology that generates 3D models (Fig. 4-5, wherein a patient’s scalp, recipient areas, and donor areas can be generated and rendered as a 3D model; Col. 11 lines 24-28, wherein 3D modifications to a scalp are based on 3D data obtained from a 3D mesh model, which is interpreted as generating a more detailed mesh model; Col. 12, lines 47-54, wherein a 3D model of a person's scalp can be generated using a 3D laser scanner, and/or stitching digital images together, which is interpreted as the 3D mesh model being created based on data from technology that generates 3D models).
Gu teaches measuring the area by counting micropolygons in 3D models and/or 3D meshes created by technologies that generate life-size 3D models (paragraph 85-86, wherein calculating and summing up the area of each small triangle to determine the area of the selected polygon is interpreted as counting and determining the total area through the cumulative sum of the areas of the micropolygon that make up the selected region of a 3D model; paragraph 75, wherein the model may be real-world entities which is interpreted as including life-size 3D models).
Neither Zhang nor Gu teaches activating the electronic device and scan the scalp using a specialized measurement application; and capturing data collected through a technology that generates life-size 3D models and form the 3D point cloud.
Katekari teaches activating the electronic device and scan the scalp using a specialized measurement application (Fig. 7A-7B, paragraph 86, wherein donor areas of a patient’s scalp is scanned using a 3D scanner designed for scanning follicular units of a scalp is interpreted as a specialized measurement application, and wherein the scanner may be activated by an operator’s command); and capturing data collected through a technology that generates life-size 3D models and form the 3D point cloud (Fig. 7B, paragraph 86, wherein the scanner captures data to produce a 3D point cloud of the surface which can be converted into a 3D model or mesh).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Zhang in view of Gu with the teachings of Katekari for this method of mapping areas of a scalp surface. Zhang teaches a method of determining and modelling the bald areas and areas with hair of a person’s scalp, and allowing a user to demarcate areas as being donor areas or recipient areas for hair transplants. Similarly, Katekari discusses scanning a person’s scalp in order to determine donor areas and recipient areas for hair transplants, involving generating 3D point clouds of a person’s scalp in order to more easily calculate the number and type of hair on a person’s body surface. While Gu does not discuss scanning or modelling a person’s scalp, or about hair transplants, it does teach a method of determining the surface area of a user inputted area of a 3D model via counting and measuring the area of micropolygons. Gu describes a method of easily determining the surface area of a specified area determined by a user in order to improve both accuracy and speed of that process. As both Zhang and Katekari describe determining donor and recipient areas of a 3D model of a person’s scalp, it would be obvious to combine these references as both Zhang and Katekari would appreciate the more efficient way of calculating those demarcated areas described in Gu.
Regarding claim 5, Zhang in view of Gu and Katekari disclose the method of claim 4. Additionally, Katekari teaches the method according to claim 4, characterized by the step of Activating the device and scanning the scalp comprising the operator turning on the electronic device equipped with three-dimensional information capture technology (Fig. 7A, paragraph 86, wherein the scanning process using a 3D scanner to capture three-dimensional information begins with the operator giving a command, which is interpreted as the operator turning on the electronic device); opening the mapping, processing, and image reconstruction application/software for specialized 3D measurement (Fig. 7A, paragraph 86, application that identifies, obtains images, and maps areas of interest of a scalp to obtain 3D point cloud data, which is interpreted as a mapping, processing, and image reconstruction application); with the software running, using the device’s camera, positioning the electronic device so that the surface of the patient’s scalp is within the technology’s field of view; capturing multiple images of the patient’s scalp from different angles, using the device’s camera, ensuring full coverage of the patient’s scalp surface that is to be measured (Fig. 7A, paragraph 86, wherein by the operator, the camera traverses a physical space to obtain multiple images of an area of interest of a scalp to create a 3D point cloud of the area of interest, wherein the camera capturing multiple images of the area of interest as the camera physically moves over the area is interpreted as capturing multiple images of the area from different angles).
The motivation to combine would be the same as that set forth for claim 4.
Regarding claim 6, Zhang in view of Gu and Katekari disclose the method of claim 5. Additionally, Katekari teaches the method according to claim 5, characterized by the electronic device equipped with three-dimensional information capture technology being, preferably, a mobile phone or tablet (Fig. 2, paragraph 53, wherein data processing system which implements the processes of the application which includes capturing 3D information is interpreted as the electronic device; paragraph 64, wherein the data processing system may be a tablet or mobile device).
The motivation to combine would be the same as that set forth for claim 4.
Regarding claim 7, Zhang in view of Gu and Katekari disclose the method of claim 4. Additionally, Katekari teaches the method according to claim 4, characterized by the step of Data Capture and Formation of the 3D Point Cloud comprising the analysis, by one of the technologies equipped with three-dimensional information capture mechanisms, of the captured images, identifying and correlating singular reference points that are matched across the various images to compute the three-dimensional spatial coordinates of the scalp, resulting in the construction of a 3D mesh or a 3D point cloud, which accurately represents the anatomy of the scanned region of the patient’s scalp (Figs. 7A-7B, wherein individual images are compiled by an application after recognition of points of interests between the 2D images and calculating the x, y, and z coordinates of those points in order to form the 3D point cloud, which is interpreted as identifying and correlating singular reference points matched between images to compute the 3D spatial coordinates of the scalp to construct a 3D point cloud).
The motivation to combine would be the same as that set forth for claim 4.
Regarding claim 8, Zhang in view of Gu and Katekari discloses the method of claim 4. Additionally, Katekari teaches the method according to claim 4, characterized by the step of Generation of the 3D Mesh (“3D MESH”) being the result of the analysis, identification, and correlation of the captured images, accurately representing the anatomy of the scanned region of the patient’s scalp (Fig. 7A-7B, paragraph 86, wherein a camera captures multiple 2D images which are compiled together to form a 3D point cloud representation of an area of interest of a scanned scalp, which is interpreted as analyzing, identifying, and correlating captured images to accurately represent the anatomy of the scanned region of the patient’s scalp, and wherein the 3D point cloud may be converted into a mesh).
The motivation to combine would be the same as that set forth for claim 4.
Regarding claim 9, Zhang in view of Gu and Katekari discloses the method of claim 4. Additionally, Zhang teaches the method according to claim 4, characterized by the step of Generation of the 3D Mesh (“3D MESH”) comprising the meticulous marking of points, delimitation, painting, and automatic recording of the region, performed by the application/software, generating a more detailed 3D mesh model of the head, which displays detailed and continuous visualizations of the scanned scalp surface (Col. 11, lines 3-28, wherein proposed hair elements, including areas of hair to be harvested from, interpreted as donor areas, and areas of hair to be transplanted to, interpreted as recipient areas, may be selected by user input freehand, which is interpreted as the operator through an application delimiting and painting the scalp region, and wherein user modifications in a 2D view is converted to corresponding 3D modifications of a 3D mesh model, which is interpreted as recording the delimiting of the scalp region onto a 3D mesh model to display the visualizations of the scanned scalp surface).
Regarding claim 10, Zhang in view of Gu and Katekari discloses the method of claim 4. Additionally, Zhang teaches the method according to claim 4, characterized by the step of Generation of the 3D Mesh (“3D MESH”) comprising the meticulous marking of points, delimitation, painting, and automatic recording of the region, performed by the application/software, generating a more detailed 3D mesh model of the head, which displays detailed and continuous visualizations of the scanned scalp surface (Col. 11, lines 3-28, wherein proposed hair elements, including areas of hair to be harvested from, interpreted as donor areas, and areas of hair to be transplanted to, interpreted as recipient areas, may be selected by user input freehand, which is interpreted as the operator through an application delimiting and painting the scalp region, and wherein user modifications in a 2D view is converted to corresponding 3D modifications of a 3D mesh model, which is interpreted as recording the delimiting of the scalp region onto a 3D mesh model to display the visualizations of the scanned scalp surface).
Regarding claim 11, Zhang in view of Gu and Katekari discloses the method of claim 10. Additionally, Katekari teaches the method according to claim 10, characterized by the 3D mesh (“3D MESH”) being generated from the point cloud, where algorithms and processing techniques are applied to connect adjacent points and form connected triangular or polygonal faces that create a continuous and detailed visual representation of the scanned scalp surface (Fig. 7B, paragraph 86, wherein the 3D point cloud can be converted into a mesh for modelling utilizing a file format such as STL, which is a commonly used and known in the art file format to represent surface geometry of 3D objects as a mesh of linked polygons by their surface normal and vertices, which is interpreted as applying processing techniques to generate a mesh to connect adjacent points and form connected polygonal faces to create a continuous and detailed visual representation of the scanned scalp surface).
The motivation to combine would be the same as that set forth for claim 4.
Regarding claim 12, Zhang in view of Gu and Katekari discloses the method of claim 11. Additionally, Katekari teaches the method according to claim 12, characterized by the 3D mesh (“3D MESH”) consisting of vertices, edges, and faces that define the geometry and topology of the scalp, where each vertex represents a specific point in three-dimensional space, and the edges and faces connect these vertices to form a continuous surface that accurately represents the characteristics of the patient's scalp (Fig. 7B, paragraph 86, wherein the 3D point cloud can be converted into a mesh for modelling utilizing a file format such as STL, which is a commonly used and known in the art file format to represent surface geometry and topology of 3D objects as a mesh of linked polygons by their surface normal and vertices, wherein vertices are separate points in 3D space, wherein edges and faces are defined as connections between vertices, and wherein the 3D STL format mesh is interpreted as consisting of vertices, edges, and faces defining the geometry and topology of the scalp).
The motivation to combine would be the same as that set forth in claim 4.
Regarding claim 13, Zhang in view of Gu and Katekari discloses the method of claim 4. Additionally, Gu teaches the method according to claim 13, characterized by the 3D mesh being composed of micropolygons that allow for the precise calculation of the surface area, even in regions with irregular curvature (paragraph 80, 85-86, wherein a set of small triangles are generated based on a selected polygon, paragraph 51 wherein the polygon is defined as a selected region of a complex 3D graphic which is interpreted as including 3D meshes), mitigating distortions caused by the irregularity and curvature of the scalp surface, providing a degree of accuracy in measuring the bald areas, as the 3D model compensates for the distortions and irregularities of the scalp surface, resulting in a highly accurate measurement of hairless areas (paragraph 106, wherein constructing small triangles results in higher accuracy in surface area calculations, which is interpreted as micropolygons resulting in highly accurate measurements of surface areas of 3D objects, which is interpreted as including models of scalps).
The motivation to combine would be the same as that set forth for claim 4.
Regarding claim 14, Zhang in view of Gu and Katekari discloses the method of claim 13. Additionally, Gu teaches the method according to claim 13, characterized by the 3D mesh being composed of micropolygons that allow for the precise calculation of the surface area (paragraph 80, 85-86, wherein a set of small triangles are generated based on a selected polygon, paragraph 51 wherein the polygon is defined as a selected region of a complex 3D graphic which is interpreted as including 3D meshes), even in regions with irregular curvature, mitigating distortions caused by the irregularity and curvature of the scalp surface, providing a degree of accuracy in measuring the bald areas, as the 3D model compensates for the distortions and irregularities of the scalp surface, resulting in a highly accurate measurement of hairless areas (paragraph 106, wherein constructing small triangles results in higher accuracy in surface area calculations, which is interpreted as micropolygons resulting in highly accurate measurements of surface areas of 3D objects, which is interpreted as including models of scalps).
The motivation to combine would be the same as that set forth for claim 4.
Regarding claim 16, Zhang teaches a Computer Program for Scalp Surface Measurement to Measure Bald Areas (recipient areas), Areas with Thinned Hair, Areas with Thick Hair (donor areas) (Fig. 1, Col. 10 line 55 – Col. 11 line 6, wherein proposed hair elements or a person’s scalp are processed, which is defined as elements where follicular units are harvested and implanted to, which is interpreted as recipient areas and donor areas, and wherein proposing a boundary curve for the proposed hair elements is interpreted as measuring the areas of a scalp), with 3D models and/or 3D meshes created by technologies that generate life-size 3D models (Col. 12, lines 47-54, wherein a 3D model of a person's scalp can be generated using a 3D laser scanner, and/or stitching digital images together, which is interpreted as technologies that generate life-size 3D models), configured to: Capture three-dimensional information of the scalp; Receive digital image data collected by technology equipped with three-dimensional information capture mechanisms (Col. 12, lines 47-54, wherein a 3D model of a person's scalp can be generated using captured data from a 3D laser scanner, and/or stitching digital images together, which is interpreted as technologies equipped with three-dimensional information capture mechanisms); Delimit, paint, and automatically record the region, generating a 3D mesh (3D MESH), which displays detailed and continuous visualizations of the scanned scalp surface; Create, from the 3D mesh (3D MESH), a continuous and detailed visual representation of the scanned scalp surface (Col. 11, lines 3-28, wherein proposed hair elements, including areas of hair to be harvested from, interpreted as donor areas, and areas of hair to be transplanted to, interpreted as recipient areas, may be selected by user input freehand, which is interpreted as the operator through an application delimiting and painting the scalp region, and wherein user modifications in a 2D view is converted to corresponding 3D modifications of a 3D mesh model, which is interpreted recording the delimiting of the scalp region onto a 3D mesh model); and Display, for viewing through the electronic device, a simulated image of the scalp (Fig. 4-5, representative views of a scalp is simulated and displayed on a user monitor).
Zhang does not teach the counting of micropolygons in 3D models and/or 3D meshes; Analyzing the captured images, identifying and correlating reference points that are matched across various images to compute the three-dimensional spatial coordinates of the scalp; Constructing a 3D point cloud, which accurately represents the geometry and topography of the scanned scalp; and measuring the area of the scalp through tactile interaction in the desired region.
Gu teaches counting of micropolygons in 3D models and/or 3D meshes (paragraph 85-86, wherein calculating and summing up the area of each small triangle to determine the area of the selected polygon is interpreted as counting the micropolygons of a selected polygon, wherein the selected polygon is defined as a region of a 3D model); and Measuring the area of the scalp through tactile interaction in the desired region (Paragraph 56, wherein a polygon demarcating a surface area on a 3D model is selected interactively by a user, which is interpreted as tactile interaction in the desired region; Paragraph 85-86, wherein the area of the polygon is determined, wherein the polygon is defined as a region of a given 3D model which is interpreted as including a model of a scalp).
Neither Zhang nor Gu teaches Analyzing the captured images, identifying and correlating reference points that are matched across various images to compute the three-dimensional spatial coordinates of the scalp; and constructing a 3D point cloud, which accurately represents the geometry and topography of the scanned scalp.
Katekari teaches Analyzing the captured images, identifying and correlating reference points that are matched across various images to compute the three-dimensional spatial coordinates of the scalp (Figs. 7A-7B, wherein individual images are compiled by an application after recognition of points of interests between the 2D images and calculating the x, y, and z coordinates of those points in order to form the 3D point cloud, which is interpreted as identifying and correlating singular reference points matched between images to compute the 3D spatial coordinates of the scalp to construct a 3D point cloud); and Constructing a 3D point cloud, which accurately represents the geometry and topography of the scanned scalp Fig. 7B, paragraph 86, wherein the scanner captures data to produce a 3D point cloud of the surface to represent the geometry and topography of a scanned scalp).
The motivation to combine would be the same as that set forth for claim 4.
Conclusion
14. Any inquiry concerning this communication or earlier communications from the examiner should be directed to JORDAN W YICK whose telephone number is (571)272-4063. The examiner can normally be reached M-F 8-5.
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/JORDAN WAN YICK/Examiner, Art Unit 2612
/Said Broome/Supervisory Patent Examiner, Art Unit 2612
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