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 .
Response to Amendment
In the preliminary remarks and amendments received on October 9th, 2024, for Application No. 18/910,779, claims 2-6, 9, 11, and 13 are amended and claims 14-18 are added. Accordingly, claims 1-18 are currently pending for examination in the application.
Priority
Acknowledgment is made of applicant’s status as a continuation (CON) of International Application No. PCT/JP2023/014303 filed on April 6th, 2023, which claims priority to foreign Patent Application No. JP2022-066635 filed on April 13th, 2022.
Information Disclosure Statement
The information disclosure statement(s) (IDS(s)) submitted on October 9th, 2024, and October 8th, 2025, is/are in compliance with the provisions of 37 CFR 1.97. Accordingly, the IDS(s) is/are being considered and attached by the examiner.
Specification
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed. The examiner respectfully suggests the following title as written in the Derwent database for Family Patent Application No. WO 2023/199847 A1: "IMAGE PROCESSING METHOD, IMAGE PROCESSING DEVICE, AND PROGRAM FOR VISUALIZING CHOROIDAL BLOOD VESSELS USING ENHANCED AND BINARIZED CHOROID IMAGES".
Claim Objections
Claims 14 and 15 are objected to because of the following informalities:
In claim 14, the examiner respectfully suggests amending the limitation “connects the end part of the first region and the end part of the second region in the first region and the second region…” to recite “connects the end part of the first region and the end part of the second region in the first region and the second region, respectively,…” to avoid confusion regarding which elements are being referred to in the phrase “in the first region and the second region” as recited in the limitation; and
In claim 15, the examiner respectfully suggests amending the phrase “the region” to recite “the discretely extracted region” to maintain consistency in claim language within the claims.
Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier, as explained in MPEP § 2181, subsection I (note that the list of generic placeholders below is not exhaustive, and other generic placeholders may invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph):
A. The Claim Limitation Uses the Term "Means" or "Step" or a Generic Placeholder (A Term That Is Simply A Substitute for "Means")
With respect to the first prong of this analysis, a claim element that does not include the term "means" or "step" triggers a rebuttable presumption that 35 U.S.C. 112(f) does not apply. When the claim limitation does not use the term "means," examiners should determine whether the presumption that 35 U.S.C. 112(f) does not apply is overcome. The presumption may be overcome if the claim limitation uses a generic placeholder (a term that is simply a substitute for the term "means"). The following is a list of non-structural generic placeholders that may invoke 35 U.S.C. 112(f): "mechanism for," "module for," "device for," "unit for," "component for," "element for," "member for," "apparatus for," "machine for," or "system for." Welker Bearing Co., v. PHD, Inc., 550 F.3d 1090, 1096, 89 USPQ2d 1289, 1293-94 (Fed. Cir. 2008); Mass. Inst. of Tech. v. Abacus Software, 462 F.3d 1344, 1354, 80 USPQ2d 1225, 1228 (Fed. Cir. 2006); Personalized Media, 161 F.3d at 704, 48 USPQ2d at 1886–87; Mas-Hamilton Group v. LaGard, Inc., 156 F.3d 1206, 1214-1215, 48 USPQ2d 1010, 1017 (Fed. Cir. 1998). Note that there is no fixed list of generic placeholders that always result in 35 U.S.C. 112(f) interpretation, and likewise there is no fixed list of words that always avoid 35 U.S.C. 112(f) interpretation. Every case will turn on its own unique set of facts.
Such claim limitation(s) is/are:
The following claim limitations are implemented on the same hardware disclosed in para. [0051] (e.g., "…the CPU 262 functions as a display control unit 204, an image processing unit 206, and a processing unit 208. The image processing unit 206 is an example of the "image acquisition unit", the "enhancement processing unit", and the "region extraction unit" of the present disclosure."):
"image acquisition unit that acquires an image…" in claim 1 described in para. [0060]; and
"enhancement processing unit that performs enhancement processing…" in claim 1 described in para. [0091]; and
"binarization processing unit that performs binarization processing…" in claim 1 described in para. [0094]; and
"region extraction unit that extracts a region…" in claim 1 described in para. [0065]; and
"connection processing unit that performs connection processing…" in claim 17 described in para. [0096]; and
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 103
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 6-13, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Hirokawa (JP2020058627A) in view of Tanabe et al. (Tanabe; US 2021/0022600 A1).
Regarding claim 1, Hirokawa discloses an image processing method performed by a processor, the method comprising:
a step of acquiring an image captured of a choroid (description, para(s). [0061], recite(s)
[0061] “The structure of the eye consists of the vitreous humor, which is surrounded by multiple layers with different structures.
The multiple layers, from the innermost to the outermost layer on the vitreous side, include the retina, choroid, and sclera.
Because red light has a longer wavelength, it can pass through the retina and reach the choroid. Therefore, the red-colored fundus image 504RG contains information about the blood vessels present in the retina (retinal blood vessels) and the blood vessels present in the choroid (choroidal blood vessels). In contrast, because green light has a shorter wavelength than red light, it only reaches the retina. Therefore, the G-color fundus image 502GG contains only information about the blood vessels present in the retina (retinal blood vessels). Therefore, by extracting retinal blood vessels from the G-color fundus image 502GG and removing retinal blood vessels from the R-color fundus image 504RG, a choroidal vascular image CLA (see Figure 13) can be obtained. Specifically, choroidal vascular images (CLA) are generated as follows.”
, where a “fundus image” is at least an image capturing a choroid (e.g., “choroidal blood vessels”));
a step of performing enhancement processing that enhances contrast in the image after it has been acquired (description, para(s). [0062], recite(s)
[0062] “…Then, the image processing control unit 206 applies an adaptive histogram equalization process (Contrast Limited Adaptive Histogram Equalization) to the image data of the red-color fundus image 504RG from which the retinal blood vessels have been removed, thereby emphasizing the choroidal blood vessels in the red-color fundus image 504RG. This creates the choroidal vascular image (CLA) shown in Figure 13. The created choroidal vascular image (CLA) is stored in the memory device 254.”
, where the “Contrast Limited Adaptive Histogram Equalization” is an enhancement processing that enhances contrast in the image (i.e., “emphasizing the choroidal blood vessels”));
a step of performing binarization processing on the image after it has been subjected to the enhancement processing (description, para(s). [0062]—see citation immediately above—, wherein description, para(s). [0066] and [0074], further recite(s):
[0066] “Choroidal vascular images may include eyelids, etc., so in step 306, the image processing control unit 206 generates a choroidal vascular image CLE (see Figure 14) in which the fundus region is cut out (eyelids, etc. are removed) from the choroidal vascular image CLA.
Choroidal vascular images (CLA) and choroidal vascular images (CLE) are images in which choroidal blood vessels are visualized by processing fundus images.”
[0074] “In step 332, the image processing control unit 206 creates a choroidal vascular binarized image (not shown) by binarizing the choroidal vascular image CLE based on a predetermined threshold value for each pixel.
This choroidal vessel binarized image visualizes the choroidal vessels (pixels in the area corresponding to the choroidal vessels are white, and pixels in areas other than the choroidal vessels are black).”
, where “binarizing the choroidal vascular image CLE” is performing a binarization process on the image); and
a step of(description, para(s). [0076] and [0113], recite(s)
[0076] “In step 334, the image processing control unit 206 assigns pixel numbers to a plurality of pixels 402, 404, 406, 408... representing choroidal blood vessels, as shown in Figure 16, and creates a blood vessel skeleton map (VSM) that associates the pixel position (or pixel coordinates) with the pixel number. ..”
[0113] “Icon 844L is an icon used to instruct the user to display choroidal vessels with a diameter of less than 300 μm in the blood vessel image display area 834 using the first color.
Icon 344M is an icon that instructs the user to display choroidal vessels with a diameter of 300 μm or more and less than 600 μm in a second color different from the first color in the blood vessel image display area 834. Icon 344H is an icon used to instruct the user to display choroidal vessels with a diameter of 600 μm or more in a third color different from the first and second colors in the blood vessel image display area 834.”
, where identifying “choroidal blood vessels” is determining regions corresponding to choroidal blood vessels in the choroid from the images).
Where Hirokawa does not explicitly disclose
…extracting a region corresponding to choroidal blood vessels in the choroid from the image after it has been subjected to the binarization processing;
Tanabe teaches in the same field of endeavor of identifying a region corresponding to choroidal blood vessels in a choroid image
…extracting a region corresponding to choroidal blood vessels in the choroid from the image after it has been subjected to the binarization processing (para(s). [0071], recite(s)
[0071] “At step 204, the image processing section 182 executes size analysis processing to analyze the size of choroidal blood vessels that appear as white in the binary image. The size analysis processing generates a first size blood vessel image in which only first size blood vessels of a size of t3 (μm) or greater are extracted, a second size blood vessel image in which only second size blood vessels of a size of from t2 (μm) up to but not including t3 (μm) are extracted, and a third size blood vessel image in which only third size blood vessels of a size of from t1 (μm) up to but not including t2 (μm) are extracted. In this example t1 is 160 μm, t2 is 320 μm, and t3 is 480 μm.”
, where each of the “extracted” choroidal blood vessels corresponding to respective sizes includes extracting regions corresponding to choroidal blood vessels in a choroid from an image after it has been subjected to binary processing (e.g., a “binary image”)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the presently filed invention to recognize that the identification of choroidal blood vessels in the image capturing a choroid after the image has been subjected to enhancement and binarization processing in the system of Hirokawa as extracting at least a region corresponding to choroidal blood vessels in the choroid from the image after it has been subjected to the binarization processing to generate the choroidal blood vessel images based on its size as taught by Tanabe above.
Regarding claim 6, Hirokawa in view of Tanabe discloses the image processing method of claim 1, wherein Tanabe further teaches the image processing method of claim 1 further comprising a step of generating a choroidal blood vessel image based on the extracted region corresponding to choroidal blood vessels (para(s). [0071]—see citation in claim 1 above—, where a “first size blood vessel image” is at least a choroidal blood vessel image generated based on the extracted region (i.e., “extracted” blood vessels) corresponding to choroidal blood vessels (e.g., of a “first size”)).
Regarding claim 7, Hirokawa in view of Tanabe discloses the image processing method of claim 6, wherein Tanabe further teaches the step of generating a choroidal blood vessel image comprises:
a step of generating a first choroidal blood vessel image based on a first region extracted from an image acquired by a first step including the step of performing enhancement processing, the step of performing binarization processing, and the step of extracting a region corresponding to choroidal blood vessels (para(s). [0071]—see citation in claim 1 above—, and para(s). [0067] and [0070] further recites:
[0067] “Note that a choroidal vascular image is generated in the following manner. …The image processing section 182 then subjects the image data of the first fundus image (R fundus image) from which the retinal blood vessels have been removed to contrast-limited adaptive histogram equalization, thereby emphasizing the choroidal blood vessels in the first fundus image (R fundus image). A choroidal vascular image as illustrated in FIG. 6 is obtained thereby. The generated choroidal vascular image is stored in the memory 164. …”
[0070] “At step 202, the image processing section 182 crops the choroidal vascular image to a fundus region (removing eyelids etc.) and subjects the fundus region to binarization processing so as to generate a binary image (see FIG. 7).”
, where the “first size blood vessel image” is at least a first choroidal blood vessel image based on a first region (e.g., “first size blood vessels”) extracted from an image acquired by a first step including the step of performing enhancement processing (e.g., “contrast-limited adaptive histogram equalization”), binarization processing (e.g., “binarization processing”), and extracting a region corresponding to choroidal blood vessels (e.g., “first size of blood vessels… are extracted”));
a step of generating a second choroidal blood vessel image based on a second region corresponding to other choroidal blood vessels that have a different diameter from the choroidal blood vessels, and that are extracted from the image by a second step that is different from the first step (para(s). [0071]—see citation in claim 1 above—, where the “second size blood vessel image” is a second choroidal blood vessel image generated based on a second region (e.g., “second size of blood vessels”) that have a different diameter (e.g., “size of from t2 (μm) up to but not including t3 (μm)”) and extracted from the image by a second step that is different from the first step (e.g., by a “second size of blood vessel”)); and
a step of generating the choroidal blood vessel image by synthesizing the first choroidal blood vessel image and the second choroidal blood vessel image (para(s). [0074], recite(s)
[0074] “At step image processing control section 206, the display control section 184 generates three images, with vascular portions of the first size blood vessel image colored red, with vascular portions of the second size blood vessel image colored green, and with vascular portions of the third size blood vessel image colored blue. Furthermore, these three blood vessel images are combined to generate a colored choroidal vascular image colored according to size. Although in this example the vascular portions of the first size blood vessel image, the vascular portions of the second size blood vessel image, and the vascular portions of the third size blood vessel image, are respectively colored red, green, and blue, other respective colors may be employed therefor.”
, where the “colored choroidal vascular image colored according to size” by “combin[ing]” at least the “first size blood vessel image” and the “second size blood vessel image” is a choroidal blood vessel image generated by synthesizing (e.g., “combin[ing]”) at least the first choroidal blood vessel image and the second choroidal blood vessel image).
Regarding claim 8, Hirokawa in view of Tanabe discloses the image processing method of claim 7, wherein Tanabe further teaches the step of generating the choroidal blood vessel image comprises:
the step of generating the first choroidal blood vessel image (para(s). [0071]—see citation in claim 1 above—, where the “first size blood vessel image” is at least a first choroidal blood vessel image);
the step of generating the second choroidal blood vessel image (para(s). [0071]—see citation in claim 1 above—, where the “second size blood vessel image” is at least a second choroidal blood vessel image);
a step of generating a third choroidal blood vessel image based on a third region corresponding to different choroidal blood vessels from the choroidal blood vessels and the other choroidal blood vessels, and that are extracted from the image by a third step that is different from the first step and the second step (para(s). [0071]—see citation in claim 1 above—, where the “third size blood vessel image” is a third choroidal blood vessel image generated based on a second region (e.g., “second size of blood vessels”) that have a different diameter (e.g., “size of from t1 (μm) up to but not including t2 (μm)”) and extracted from the image by a third step that is different from the first and second step (e.g., by a “third size of blood vessel”)); and
a step of generating the choroidal blood vessel image by synthesizing the first choroidal blood vessel image, the second choroidal blood vessel image and the third choroidal blood vessel image (para(s). [0074]—see similar limitation in claim 7 above—, where the “colored choroidal vascular image colored according to size” by “combin[ing]” the “three blood vessel images”, is a choroidal blood vessel image generated by synthesizing (e.g., “combin[ing]”) at least the first choroidal blood vessel image (e.g., “first size blood vessel image”), the second choroidal blood vessel image (e.g., “second size blood vessel image”), and the third choroidal blood vessel image (e.g., “third size blood vessel image”)).
Regarding claim 9, Hirokawa in view of Tanabe discloses the image processing method of claim 1, wherein Hirokawa further discloses the image processing method of claim 1 further comprising a step of generating a stereoscopic image of choroidal blood vessels based on a plurality of choroidal blood vessel images (description, para(s). [0082], recite(s)
[0082] “…The vascular skeleton image VS is projected onto this simulated eyeball surface after inverse stereo transformation. This is because the UWF-SLO image itself is a stereo projection of the eyeball onto a two-dimensional plane. While the peripheral areas of UWF-SO images and vascular skeleton images (VS) exhibit distortion due to stereo conversion, this distortion can be eliminated by performing inverse stereo conversion and projecting it onto a simulated eyeball surface. Since the blood vessel diameter is calculated with distortion removed, a value close to the actual blood vessel diameter can be obtained. …”
, where performing a “stereo projection” of either the “UWF-SO images” or “vascular skeleton images (VS)” is generating a stereoscopic image of choroidal vessels based on a plurality of choroidal blood vessel images (e.g., the “UWF-SO images” and/or “vascular skeleton images”)).
Regarding claim 10, Hirokawa in view of Tanabe discloses the image processing method of claim 8, wherein Hirokawa further discloses the image processing method of claim 8 further comprising a step of generating a stereoscopic image of choroidal blood vessels based on the first choroidal blood vessel image and the second choroidal blood vessel image (description, para(s). [0082]—see citation in claim 9 above—, where performing a “stereo projection” of at least “vascular skeleton images (VS)” is generating a stereoscopic image of choroidal vessels based on at least the first choroidal blood vessel image and the second choroidal blood vessel image because description, para(s). [0113]—see citation in claim 1 limitation “a step of extracting…” above—, and [0124]—see below—, further discloses that the “vascular skeleton images” are obtained from “choroidal vessels” obtained from the “binarized” choroidal vessels of at least a first choroidal blood vessel image (e.g., “first color” blood vessel image displayed) and a second choroidal blood vessel image (e.g., “second color” blood vessel image displayed):
[0124] “…In step 902 of Figure 33, the same process as in step 322 of Figure 7 is performed. In other words, choroidal vessels included in the choroidal vessel binarized image (Figure 34) are identified, and a vascular skeleton image VS and a vascular network VN are created for the choroidal vessels 912. …”
).
Regarding claim 11, Hirokawa in view of Tanabe discloses the image processing method of claim 1, wherein Hirokawa further discloses the step of acquiring the image comprises scanning a region of a fundus including at least a vortex vein (description, para(s). [0024] and [0115], recite(s)
[0024] “…The imaging device 14 includes an SLO unit 18 and an OCT unit 20, and acquires fundus images of the fundus of the eye under examination 12.
Hereinafter, the two-dimensional fundus image acquired by the SLO unit 18 will be referred to as the SLO image. Furthermore, cross-sectional images and frontal images (en-face images) of the retina created based on OCT data acquired by the OCT unit 20 are also referred to as OCT images.”
[0115] “The choroidal analysis tool display area 806 is a field where icons for selecting multiple choroidal analyses are displayed. It includes vortex vein location icons 852… The blood vessel diameter icon 856 instructs the system to display the analysis results regarding the diameter of the choroidal vessels. The vortex vein/macula/optic disc icon 858 indicates that the system should display the analysis results showing the positions of the vortex veins, macula, and optic disc. The choroidal analysis report icon 860 instructs the system to display the choroidal analysis report.”
, where identifying “vortex vein location[s]” by analyzing “fundus images” is at least acquiring the image comprises of scanning a region of a fundus (e.g., “fundus of the eye under examination”) including at least the vortex vein).
Regarding claim 12, the claim recites similar limitations to claim 1 but in the form of a device. Hirokawa discloses said device, comprising: an image acquisition unit…; an enhancement unit…; a binarization processing unit…; and a region extraction unit (description, para(s). [0057], recite(s)
[0057] “…The image processing program includes display control functions, image processing control functions, and processing functions. When the CPU 262 executes an image processing program having each of these functions, the CPU 262 functions as a display control unit 204, an image processing control unit 206, and a processing unit 208, as shown in Figure 6. The image processing control unit 206 is an example of a "choroidal vessel image acquisition unit," a "specification unit," a "calculation unit," a "storage processing unit," a "first specification unit," a "second specification unit," and a "control unit."”
, where the “image processing control unit” (e.g., “CPU”) is at least each of these units of said device). Therefore, claim 12 is rejected for similar rationale and reasoning as claim 1 (see the analysis for claim 1 above).
Regarding claim 13, recites similar limitations to claim 1 but in the form of a non-transitory recording medium. Hirokawa discloses said non-transitory recording medium (description, para(s). [0054], recite(s)
[0054] “…The storage device 254 stores the image processing program, which will be described later. The image processing program may also be stored in ROM 264. The storage device 254 and ROM 264 are examples of “storage media” in the technology of this disclosure.”
, where the “storage device” is at least a non-transitory recording medium (e.g., “ROM”)). Therefore, claim 13 recites similar limitations to claim 1 and is rejected for similar rationale and reasoning (see the analysis for claim 1 above).
Regarding claim 16, Hirokawa in view of Tanabe discloses the image processing method of claim 1, wherein Hirokawa further discloses the step of performing enhancement processing enhances thin choroidal blood vessels within the choroid (description, para(s). [0062]—see citation in claim 1 limitation “a step of performing enhancement…” above—and description para(s). [0076]—see citation in claim 1 limitation “a step of extracting...” above—, where the step of enhancement process (e.g., “Contrast Limited Adaptive Histogram Equalization”) enhances (e.g., “”emphasiz[es]”) all “choroidal blood vessels” within the choroid includes thin choroidal blood vessels (e.g., “choroidal vessels with a diameter of less than 300 μm“) is the enhancement processing enhancing thin choroidal blood vessels within the choroid).
Claims 2, 4, and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over Hirokawa in view of Tanabe as applied to claims 1, 12, and 13 above, and further in view of Leahy et al. (Leahy; “Mapping the 3D Connectivity of the Rat Inner Retinal Vascular Network Using OCT Angiography,” 2015).
Regarding claim 2, Hirokawa in view of Tanabe discloses the image processing method of claim 1, wherein Leahy teaches in the same field of endeavor of extracting regions corresponding to blood vessels from a binarized image the step of extracting a region corresponding to choroidal blood vessels includes a step of performing connection processing that connects a plurality of the extracted regions, which are choroidal blood vessels that have been extracted in a severed state (2nd para. on pg. 5785, 2nd para. of subheading “skeletonization” on pg. 5786, and subheading “skeletonization” on pg. 5787, recite(s)
[2nd para. on pg. 5785] “Optical imaging through the transparent ocular media offers the opportunity to quantitatively assess vasculature noninvasively in vivo. The blood vessels of the inner retina exhibit a characteristic three-dimensional (3D) layered structure, with superficial, intermediate, and deep vessel layers, corresponding to the ganglion cell layer/nerve fiber layer, the inner plexiform layer, and the outer plexiform layer, respectively.9 A fundamental limitation of 2D photography-based techniques, such as fluorescein angiography,10 is the lack of depth discrimination,11 due to overlapping signals from the individual retinal layers and the choroid”
[2nd para. of subheading “skeletonization” on pg. 5786] “Skeletonization errors typically take the form of small erroneous branches occurring due to inhomogeneities in the structure of the binary vessel mask, and gaps in segmented branches (e.g., due to low signal contrast) that are manifested as unconnected endpoints in the skeleton. …”
[subheading “skeletonization” on pg. 5787] “…We developed a suite of automatic and manually-guided methods to correct the vascular skeleton, as illustrated in Figure 2. …Figure 2C illustrates the joining of two unconnected endpoints using a shortest-path algorithm. Figure 2D illustrates resolution of an unconnected endpoint, using extrapolation of the endpoint’s trajectory. Full details of the skeleton correction methods can be found in the Supplementary Methods.”
, where the “joining of two unconnected endpoints” is performing connection processing that connects a plurality of extracted regions that have been extracted in a severed state (e.g., “gaps in segmented branches”)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the presently filed invention to modify the system of Hirokawa in view of Tanabe to incorporate connection processing that connects a plurality of extracted regions, which are choroidal blood vessels that have been extracted in a severed state, to correct errors in inhomogeneities of the choroidal blood vessels in the plurality of extracted regions extracted from the image capturing a choroid in the system of Hirokawa in view of Tanabe as taught by Leahy above.
Regarding claim 4, Hirokawa, as modified by Tanabe and Leahy, discloses the image processing method of claim 2, wherein Leahy further teaches the step of performing connection processing extends, in a longitudinal direction, each of a first region and a second region that are the plurality of the extracted regions, and connects an end part of the first region and an end part of the second region by the extension (subheading “skeletonization” on pg. 5787—see citation in claim 2 above—, where the “joining of two unconnected endpoints” is extending in a longitudinal direction (e.g., “endpoint’s trajectory”) each of a first region and a second region by connecting an end part of the first region (e.g., the first of the “two unconnected endpoints”) and an end part of the second region (e.g., the second of the “two unconnected endpoints”)).
Regarding claim 17, Hirokawa in view of Tanabe discloses the image processing device of claim 12, wherein Leahy teaches in the same field of endeavor of extracting regions corresponding to blood vessels from a binarized image the region extraction unit that extracts a region corresponding to choroidal blood vessels includes a connection processing unit that performs connection processing that connects a plurality of the extracted regions (2nd para. on pg. 5785, 2nd para. of subheading “skeletonization” on pg. 5786, and subheading “skeletonization” on pg. 5787—see similar limitation in claim 2 above—, where the “joining of two unconnected endpoints” is performing connection processing that connects a plurality of extracted regions (e.g., “segmented branches”)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the presently filed invention to modify the system of Hirokawa in view of Tanabe to incorporate a connection processing unit that performs connection processing that connects a plurality of the extracted regions to correct errors in inhomogeneities of the choroidal blood vessels in the plurality of extracted regions extracted from the image capturing a choroid in the system of Hirokawa in view of Tanabe as taught by Leahy above.
Regarding claim 18, Hirokawa in view of Tanabe discloses the program of claim 13, wherein Leahy teaches in the same field of endeavor of extracting regions corresponding to blood vessels from a binarized image the step of extracting a region corresponding to choroidal blood vessels includes a step of performing connection processing that connects a plurality of the extracted regions (2nd para. on pg. 5785, 2nd para. of subheading “skeletonization” on pg. 5786, and subheading “skeletonization” on pg. 5787—see similar limitation in claim 2 above—, where the “joining of two unconnected endpoints” is performing connection processing that connects a plurality of extracted regions (e.g., “segmented branches”)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the presently filed invention to modify the system of Hirokawa in view of Tanabe to incorporate performing connection processing that connects a plurality of the extracted regions in the step of extracting a region corresponding to choroidal blood vessels to correct errors in inhomogeneities of the choroidal blood vessels in the plurality of extracted regions extracted from the image capturing a choroid in the system of Hirokawa in view of Tanabe as taught by Leahy above.
Claims 3 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Hirokawa, as modified by Tanabe and Leahy, as applied to claim 2 above, and further in view of Liu et al. (Liu; CN 111899272 A).
Regarding claim 3, Hirokawa, as modified by Tanabe and Leahy, discloses the image processing method of claim 2, wherein Leahy further teaches the step of performing connection processingsecond region(subheading “skeletonization” on pg. 5787—see citation in claim 2 above—, where the “joining of two unconnected endpoints” is connecting an end part of the first region (e.g., the first of the “two unconnected endpoints”) and an end part of the second region (e.g., the second of the “two unconnected endpoints”)).
Where Hirokawa, as modified by Tanabe and Leahy, does not specifically disclose
performs expansion processing that expands each of a first region and a second region that are the plurality of the extracted regions, and connects an end part of the first region and an end part of the second region by the expansion processing;
Liu teaches as in the same field of endeavor of performing connection processing connecting an end part of a first region and an end part of a second region
performs expansion processing that expands each of a first region and a second region that are the plurality of the extracted regions, and connects an end part of the first region and an end part of the second region by the expansion processing (para(s). [0068], [0069], and [0071], recite(s)
[0068] “The blood vessel segmentation images obtained from the above steps contain many broken sections within the blood vessels. It is necessary to connect these sections to form a complete and accurate blood vessel image. …”
[0069] “…When performing the connection operation, it is necessary to ensure that the first and last pixels in each direction must belong to the blood vessel pixel, that is, the pixel value is 1 in the binary image. If a direction does not meet this condition, the direction is discarded.”
[0071] “…The center pixel is the blood vessel pixel, and the squares with diagonal lines are the broken parts. This kind of break can occur anywhere in that direction.
The connection operation to be performed is to convert the pixels at the break point into blood vessel pixels, that is, to convert the pixels with a value of 0 under the 30° direction coverage into pixels with a value of 1.”
, where the “connection operation” includes filling in pixel regions in “broken sections” between blood vessel segments is performing connection processing that includes performing expansion processing that expands each of a first region and a second region (e.g., “converting pixels with a value of 0… into pixels with a value of 1” such that the first and second regions are expanded to connect as one continuous region) and connects end parts of the first and second regions (e.g., “first and last pixels in each direction” of the broken blood vessel section) by the expansion processing (e.g., the filling of the broken region with “pixels with a value of 1”)).
Since each of Hirokawa and Tanabe disclose displaying images of the vasculature of choroidal blood vessels (see the citations for claim 1 limitation “a step of extracting…” above), it would have been obvious to one of ordinary skill in the art before the effective filing date of the presently filed invention to modify the system of Hirokawa, as modified by Tanabe and Leahy, to incorporate performing connection processing by performing expansion processing that expands each of a first region and a second region that are the plurality of the extracted regions, and connects an end part of the first region and an end part of the second region by the expansion processing, to connect any broken choroidal blood vessel sections to form a more complete and accurate choroidal blood vessel image as taught by Liu above (para(s). [0068]—see citation above).
Regarding claim 14, Hirokawa, as modified by Tanabe, Leahy, and Liu, discloses the image processing method of claim 3, wherein Leahy teaches in the same field of endeavor of extracting regions corresponding to blood vessels from a binarized image the step of performing connection processing connects the end part of the first region and the end part of the second region in the first region and the second region that are within a predetermined range (subheading “skeletonization” on pg. 5787—see similar limitation in claim 1 above—, where “joining two unconnected endpoints using a shortest-path algorithm” is performing connection processing that connects the end part of the first region (e.g., an “endpoint” of a first vessel in the “vascular skeleton”) and the end part of the second region that are within a predetermined range (e.g., “shortest-path”)).
Claims 5 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Hirokawa in view of Tanabe as applied to claim 1 above, and further in view of Nitta (WO 2022/196583 A1).
Regarding claim 5, Hirokawa in view of Tanabe discloses the image processing method of claim 1, wherein Nitta teaches in the same field of endeavor of extracting regions corresponding to blood vessels from a binarized image the step of extracting a region corresponding to choroidal blood vessels includes a step of removing a discretely extracted region from within the image (description, para(s). [0121-0122], recite(s)
[0121] “Figure 23 shows the binarized image obtained by binarizing the original image.
The evaluation value calculation unit 520 reduces the width of the blood vessel regions (white areas in the figure) appearing in the binarized image to a width of 1 pixel each (skeletonization) to generate a reduced image.”
[0122] “Figure 24 shows a reduced image in which the width of the vascular region in the binarized image has been reduced.
The evaluation value calculation unit 520 removes objects from the reduced image whose corresponding number of pixels is below a predetermined threshold. Furthermore, areas from which objects have been removed in the image are treated as non-vascular areas (background areas). The predetermined threshold is, for example, 30. Figure 25 shows the image after object removal (post-removal image). …”
, where removing binarized areas “below a predetermined threshold” is removing at least a discretely extracted region from within the image (e.g., “areas” in the “binarized image” corresponding to “non-vascular areas”)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the presently filed invention to modify the system of Hirokawa in view of Tanabe to incorporate removing a discretely extracted region from within the image in the step of extracting a region corresponding to choroidal blood vessels to remove non-vascular regions in the extracted regions in the image capturing choroidal blood vessels as taught by Nitta above.
Regarding claim 15, Hirokawa, as modified by Tanabe and Nitta, discloses the image processing method of claim 5, wherein Nitta further teaches the step of removing the region includes removing a region having a predetermined area or less (description, para(s). [0121-0122]—see citations in claim 5 above—, where removing binarized areas “below a predetermined threshold” is removing a region having a predetermined area or less).
Conclusion
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/J.Z.Y./Examiner, Art Unit 2666
/MING Y HON/Primary Examiner, Art Unit 2666
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