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 .
Drawings
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The drawings are objected to because Fig. 2 is currently presented in low resolution such that it is difficult to properly read the text in Fig. 2 (see below).
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Specification
The disclosure is objected to because it contains an embedded hyperlink and/or other form of browser-executable code (see paragraph [0092] from the corresponding US Publication US 2024/0029458). Applicant is required to delete the embedded hyperlink and/or other form of browser-executable code; references to websites should be limited to the top-level domain name without any prefix such as http:// or other browser-executable code. See MPEP § 608.01.
Claim Objections
Claims 1 and 14 are objected to because of the following informalities:
Claim 1 recites a series of steps in a method, but the verb tenses are inconsistent. For example, step ii and step iii recite a calculation and removal step, but steps v. and vi. recite classifying (instead of classification) and determining (instead of determination). The Examiner recommends that consistent terminology be used.
Claim 1 recites “providing a microscopic image of platelets”, whereas claim 14 recites “after taking a microscope image”. The Examiner recommends that consistent terminology be used.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
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.
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.
Claims 1-14 are 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. The claims are generally narrative and indefinite, failing to conform with current U.S. practice. They appear to be a literal translation into English from a foreign document and are replete with grammatical and idiomatic errors, which result in difficulty in properly interpreting the claims. The Examiner lists below several of the present issues with the claim language.
Claim 1: There are several images recited in this claim limitations (i.e., “platelet count based on images of a suspension”, “providing a grayscale microscopic image of platelets”, “bright region analysis of an image and dark region analysis of an image”, etc.). Further clarification is required to ensure that each reference to an image has proper antecedent basis, such that it is clear which image is being analyzed and how the image is being analyzed. This applies to all dependent claims that refer to an image as well, as it is unclear which image is being analyzed in the dependent claims.
Claim 1: step ii. Recites “calculation… its convex hull and filtering the obtained results by shape”. It is unclear what “its” is referring to, and the term “the obtained results” lacks antecedent basis.
Claim 1: The term “nesting” is unclear in the limitation “removal of the nesting light and dark regions”, as the current claim language in claim 1 does not suggest how the light and dark regions would be super imposed/merged/combined or nested within each other, especially considering that step i. recites “bright region analysis of an image and dark region analysis of an image” (i.e., two different, distinct images).
Claim 1: Step iv. Recites “identification of the aggregates”, wherein the term “the aggregates” lacks antecedent basis. This applies for all dependent claims which also refer to an “aggregate”.
Claim 1: Step iv. recites a substep “graph analysis – connected components”, where it is unclear how the substep should be interpreted. Furthermore, the substep "circularity analysis” needs further clarification, as it is unclear what the circularity analysis is being performed on.
Claim 1: The preamble of the claim discloses images of platelets, but later steps v. and vi. disclose classifying “cells as platelets and other blood components”. There is no antecedent basis for the term “cells” (as platelets, as known by one skilled in the art and as defined in [0002] of the Applicant’s specification (cited from US 2024/0029458), are only fragments of cells and not considered full cells.). Furthermore, the term “other blood components” is indefinite as it is unclear what the other blood components are referring to.
Claim 1: The term “masks” in step vi. is lacking antecedent basis, as it is unclear what the term “masks” is referring to. This also applies to all other dependent claims which also refer to a “masks”/“cell masks”.
Claim 4: There is no antecedent basis for the term “the result” as there are several results produced by the method disclosed in claim 1. Furthermore, it is unclear which “area” is referred to of the Bürker chamber (i.e., the whole surface, part of the chamber defined by the lines?).
Claims 5 and 6 recite limitations using the language “preferably”, however the term “preferably” is indefinite as it does not define the scope of the claim.
Claim 9: The term “from two images” lacks antecedent basis. Furthermore, it is unclear what the index image should be, and what “consecutive numbers represent cell masks” refers to.
Claim 11: It is unclear what the terms “white cells” and “aggregates” (i.e., aggregates of what?) refers to. The Examiner notes that claim 13 refers to “platelet aggregates”, however other portions of the claim set only refer to “aggregates”.
Claim 13: It is unclear what “undesired masks” refers to – what is considered to be “undesired”?
The Examiner emphasizes that as a whole, the claim set has several issues with antecedent basis, indefinite terms, or inconsistent terminology which is preventing proper interpretation of the claims. The Examiner recommends that the entire claim set be reviewed and corrected such that all terms are consistently used and properly referenced to.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-14 are rejected under 35 U.S.C. 101 because the claimed invention is
directed to an abstract idea without reciting elements that amount to significant more than
the abstract idea. The rationale for this rejection, under MPEP § 2106, for this finding is
explained below.
Step 1: Under step 1, the claims are analyzed to determine if the claim is directed to a
process, machine, article of manufacture, or composition of matter. For the claims in question,
claim 1 is directed towards a process for determining platelet count.
Step 2A, Prong 1: Under step 2A, prong 1, the claims are evaluated to determine if the
claim recites a judicial exception, which includes the laws of nature, physical phenomena, or an
abstract idea. For independent claim 1, the Examiner notes below the underlined and bolded limitations:
Claim 1. A method for automatically determining a platelet count based on images of a suspension of peripheral blood smears, comprising providing a grayscale microscopic image of platelets, segmentation and analysis of the image, wherein the step of segmentation and analysis of the image comprises:
i. bright region analysis of an image and dark region analysis of an image, comprising the detection of distinctive bright regions and dark regions in an image using a maximally stable external regions algorithm (MSER);
ii. calculation, for each found light region and dark region, its convex hull and filtering the obtained results by shape;
iii. removal of the nesting light and dark regions;
iv. Identification of the aggregates, wherein this step comprises:
dilation of the dark regions of the image;
graph analysis - connected components;
circularity analysis;
v. classifying cells as platelets and other blood components;
vi. determining the number of platelets and their masks.
In the analysis provided above, the underlined limitations are directed towards a mathematical concept, as they involve some sort of calculation or usage of an algorithm. The limitations in bold are directed towards a mental process, such that they are limitations which could be performed by an individual in their mind. The process of identifying or classifying cells, aggregates, or platelets in an image is a process which can be performed by an individual skilled in the art.
Step 2A, Prong 2: Under step 2A, prong 2, the claims are evaluated to determine
whether the claim as a whole integrates the recited judicial exception into a practical application
of the exception (see MPEP 2106.04(d)). More specifically, the claim is evaluated to determine if the claim recites additional elements that integrate the judicial exception in to a practical application. The examiner notes that MPEP 2106.05(a) -(c) and (e) generally concern limitations that are indicative of integration, whereas 2106.05(f)-(h) generally concern limitations that are not indicative of integration.
In regards to independent claim 1, the additional limitations that are not annotated in the above analysis are generically described and relate to the general field of image processing, and do not constitute integration into a practical application.
In regards to dependent claims 2-14, the additional limitations are directed towards extra-solution activity or are broadly and generically described relating to substeps required to perform the judicial exception, and do not constitute integration into a practical application.
The examiner emphasizes MPEP 2106.05(a), which states that a limitation is indicative of integration into a practical application if the limitation identifies a manner in which an improvement is explicitly and specifically achieved and recited in the claims. The current claim language all are recited at a high level of generality and/or are presented with grammatical/idiomatic errors which prevent the claim reciting an explicit improvement, which do not serve to integrate the limitations in view of MPEP 2106.05(f), and furthermore nothing precludes the current limitations from being interpreted under the mental processes grouping.
Step 2B: Under step 2B, the claims are evaluated as a whole to determine if it amounts to
significantly more than the recited exception (i.e., whether any additional element, or
combination of additional elements, adds an inventive concept to the claim). The considerations
of step 2A, prong 2 and step 2B overlap, but differ in that 2B also requires considering the claim
as a whole/combination of limitations, and with reference to MPEP 2106.05(d) whether the
claims feature any “specific limitation(s) other than what is well - understood, routine,
conventional activity in the field” (WURC). The Examiner asserts that, even when considered in combination, the additional elements of claims 1-14 represent the steps required to automate the process of identifying and classifying platelets and cells, at a high level of generality that is generally linked to the field of applying image processing techniques to cell images, and therefore does not provide a specifically recited inventive concept.
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.
Claims 1, 3, 5, 7, 10, and 14 are rejected as being unpatentable over Meimban et al. (“Blood Cells Counting using Python OpenCV”, Year: 2018, DOI: 10.1109/ICSP.2018.8652384; hereinafter “Meimban”) in view of Salahat et al. (US 2016/0113546; hereinafter “Salahat”) in view of Arteta et al. (“Detecting Overlapping Instances in Microscopy Images using Extremal Region Trees”, Year: 2015, DOI: https://doi.org/10.1016/j.media.2015.03.002; hereinafter “Arteta”) in view of Tareef et al. (“Automated Three-Stage Nucleus and Cytoplasm Segmentation of Overlapping Cells”, Year: 2014, DOI: 10.1109/ICARCV.2014.7064418 ; hereinafter “Tareef”) in view of Shahzad et al. (“Robust Method for Semantic Segmentation of Whole-Slide Blood Cell Microscopic Images”, Year: 2020, DOI: https://doi.org/10.1155/2020/4015323; hereinafter “Shahzad”).
Regarding Claim 1, Meimban discloses a method for automatically determining a platelet count based on images of a suspension of peripheral blood smears (A. Image Uploading, Fig. 2, Meimban discloses analyzing images of a blood cell specimen to determine a platelet count.), comprising providing a grayscale microscopic image of platelets, segmentation and analysis of the image, wherein the step of segmentation and analysis of the image comprises (Section D. Blob Detection, Meimban performs image analysis on a grayscale image of cells, wherein the grayscale image includes platelets.):
ii. calculation, for each found light region and dark region, its convex hull and filtering the obtained results by shape (Section D. Meimban discloses using the OpenCV function SimpleBlobDetector to detect and filter blobs.);
vi. determining the number of platelets and their masks (Abstract, Section E. Cell Counting, Meimban discloses determining counts for platelets, red blood cells, and white blood cells.).
Meimban does not disclose:
i. bright region analysis of an image and dark region analysis of an image, comprising the detection of distinctive bright regions and dark regions in an image using a maximally stable external regions algorithm (MSER);
iii. removal of the nesting light and dark regions;
iv. Identification of the aggregates, wherein this step comprises:
dilation of the dark regions of the image;
graph analysis - connected components;
circularity analysis;
v. classifying cells as platelets and other blood components;
Salahat discloses:
i. bright region analysis of an image and dark region analysis of an image, comprising the detection of distinctive bright regions and dark regions in an image using a maximally stable external regions algorithm (MSER) ([0038], Salahat discloses utilizing an MSER algorithm to detect bright MSERs and dark MSERs (i.e., bright regions and dark regions of an image).);
Meimban and Salahat are considered to be analogous to the claimed invention as they are in the same field of analyzing biological/physiological images. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Meimban such that the images obtained by Meimban were processed using the MSER algorithm to generate bright MSER images and dark MSER images, which are then further processed by Meimban’s methods of using the SimpleBlobDetector to determine platelet and cell counts. The motivation for this combination being the ability to take into consideration details that may exist in bough dark and bright regions of the image.
Meimban in view of Salahat does not teach:
iii. removal of the nesting light and dark regions;
iv. Identification of the aggregates, wherein this step comprises:
dilation of the dark regions of the image;
graph analysis - connected components;
circularity analysis;
v. classifying cells as platelets and other blood components;
Arteta discloses:
iii. removal of the nesting light and dark regions (Abstract, 4. Model Overview, Arteta discloses tree-based method to select non-overlapping structures (i.e., removal of nesting regions));
Meimban, Salahat, and Arteta are considered to be analogous to the claimed invention as they are in the same field of analyzing biological/physiological images. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Meimban in view of Salahat such that after the dark and bright images are processed by the methods of Meimban in view of Salahat, Arteta’s process of removing non-overlapping structures is used prior to determining the cell and platelet counts. The motivation for this combination being the ability to remove common regions which appear in both bright and dark images, as they may lead to erroneous cell and platelet counts.
Meimban in view of Salahat in view of Arteta does not teach:
iv. identification of the aggregates, wherein this step comprises:
dilation of the dark regions of the image;
graph analysis - connected components;
circularity analysis;
v. classifying cells as platelets and other blood components;
Tareef discloses:
iv. identification of the aggregates, wherein this step comprises (C. Overlapping Cervical Cell Segmentation Based on Gradient Thresholding, Edge and Region Integration, Tareef discloses identifying overlapping cells (i.e., aggregated cells)):
dilation of the dark regions of the image (C. Overlapping Cervical Cell Segmentation Based on Gradient Thresholding, Edge and Region Integration, Tareef discloses performing a closing morphological process (which involves a dilation process) in order to identify overlapping cells.);
graph analysis - connected components (C. Overlapping Cervical Cell Segmentation Based on Gradient Thresholding, Edge and Region Integration, Fig. 2, Tareef discloses edge maps of cells which are connected together.);
circularity analysis (C. Overlapping Cervical Cell Segmentation Based on Gradient Thresholding, Edge and Region Integration, Equation 1, Tareef discloses calculating a circularity value to determine segmentation.);
Meimban, Salahat, Arteta, and Tareef are considered to be analogous to the claimed invention as they are in the same field of analyzing biological/physiological images. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Meimban in view of Salahat in view of Arteta such that it incorporated the aggregate detection methods disclosed by Tareef. The motivation for this combination being the ability to detect aggregates of cells/platelets, which may lead to erroneous cell/platelet counts.
Meimban in view of Salahat in view of Arteta in view of Tareef does not teach
v. classifying cells as platelets and other blood components;
Shahzad discloses:
v. classifying cells as platelets and other blood components (3. Dataset Preparation, 4.1. Preprocessing, Fig. 6, Shahzad discloses performing semantic segmentation and generating masks which represent each blood cell type (white blood cells, red blood cells, and platelets).);
Meimban, Salahat, Arteta, Tareef, and Shahzad are considered to be analogous to the claimed invention as they are in the same field of analyzing biological/physiological images. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Meimban in view of Salahat in view of Arteta in view of Tareef such that it incorporated the specific classification methods disclosed by Shehzad. The motivation for this combination being the ability to specifically distinguish individual cell types and platelets in a cell image, as this will aid in the counting of cells and platelets (both for automatic counting and also manual counting).
Regarding Claim 3, Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad teaches the method according to claim 1, wherein the microscope image is taken at 100x magnification (A. Image Uploading, Meimban discloses using 100x magnification images.).
Regarding Claim 5, Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad teaches the method according to claim l wherein the conversion of the colour image to grayscale is carried out by transferring the loaded image from the RGB colour space to the HSV colour space and selecting a channel (B. Color Filtering, Meimban discloses convering an image from RGB to HSV, from which the HSV image is then used to produce a grayscale value image (see Section D. Blob Detection).), wherein a third channel is preferably used as a single channel image.
Regarding Claim 7, Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad teaches the method according to claim l wherein the filtering of the obtained results by shape in step [ii.] is performed such that some masks identified by the MSER algorithm with a circularity factor lower than the threshold value are removed (Section D. Meimban discloses using the OpenCV function SimpleBlobDetector to detect and filter blobs. The Examiner notes that Meimban specifically discloses configuring the parameters of the SimpleBlobDetector (which includes a circularity parameter) such that it optimally classifies platelet images, which involves the process of filtering out portions of an image which do not meet the circularity parameter (i.e., threshold).).
Regarding Claim 10, Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad teaches the method according to claim l, wherein the platelet aggregates are determined based on the number of masks present in a given common component after a morphological close process performed on the previously identified masks (C. Overlapping Cervical Cell Segmentation Based on Gradient Thresholding, Edge and Region Integration, Tareef discloses performing a closing morphological process (which involves a dilation process) in order to identify overlapping cells.).
Regarding Claim 14, Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad teaches the method according to claim l, wherein after taking a microscope image, it is loaded into an analysis program and a conversion of the colour image to a grayscale image is performed (A. Image Uploading, Meimban discloses using a Python based program to perform image analysis.).
Claim 2 is rejected as being unpatentable over Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad in view of Lindberg and Olesen. (US 2008/0019584; hereinafter “Lindberg”).
Regarding Claim 2, Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad teaches the method according to claim 1
Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad does not teach wherein the provided microscopic image of the platelets is taken of a suspension of peripheral blood smear placed in a Bürker chamber adapted for manual cell counting.
Lindberg teaches wherein the provided microscopic image of the platelets is taken of a suspension of peripheral blood smear placed in a Bürker chamber adapted for manual cell counting ([0003], [0011], Lindberg discloses a manual counting procedure of cells using a Bürker chamber.).
Meimban, Salahat, Arteta, Tareef, Shahzad, and Lindberg are considered to be analogous to the claimed invention as they are in the same field of analyzing biological/physiological images. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad such that the blood sample obtained by Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad was obtained using a Bürker chamber as disclosed by Lindberg. The motivation for this combination being the ability to use a specific type of cell counting chamber which includes gridlines to aide in counting of cells and platelets.
Claim 6 is rejected as being unpatentable over Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad in view of ImageMagick (https://legacy.imagemagick.org/Usage/morphology/#basic, Year: 2020, hereinafter “ImageMagick”).
Regarding Claim 6, Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad teaches the method according to claim 1.
Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad does not teach wherein after conversion of an image to a grayscale image, two complementary images are formed therefrom, wherein a first image is formed by dilation of the grayscale image with a disk-type kernel, preferably with a radius of 8, and a second image is generated by erosion of the grayscale image.
ImageMagick discloses wherein after conversion of an image to a grayscale image, two complementary images are formed therefrom, wherein a first image is formed by dilation of the grayscale image with a disk-type kernel, preferably with a radius of 8, and a second image is generated by erosion of the grayscale image (Basic Morphology Methods, ImageMagick discloses generating images using Erode and Dialate based on a shape kernel, wherein ImageMagick allows for a “disk-type” kernel to be used.).
Meimban, Salahat, Arteta, Tareef, Shahzad, and ImageMagick are considered to be analogous to the claimed invention as they are in the same field of analyzing images. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad such that the grayscale images, taught by Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad, were processed using the image morphology methods disclosed by ImageMagick in order to produce an eroded image and dilated image. The motivation for this combination is the ability to clarify the image by removing perturbations and increasing detail in important regions of the image, which is beneficial when attempting to classify and count cells and platelets.
Claim 8 is rejected as being unpatentable over Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad in view of Livingston and Yue (US 2020/0393355; hereinafter “Livingston”).
Regarding Claim 8, Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad teaches the method according to claim 7.
Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad does not teach wherein a threshold circularity factor of 0.6 is used.
Livingston teaches wherein a threshold circularity factor of 0.6 is used ([0039], Livingston discloses utilizing a circularity of 0.6 as a metric for identifying non-cell particles.).
Meimban, Salahat, Arteta, Tareef, Shahzad, and Livingston are considered to be analogous to the claimed invention as they are in the same field of analyzing biological/physiological images. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad such that the filtering of certain masks utilized the specific circularity threshold disclosed by Livingston. The motivation for this combination being the ability to use a tested threshold which can effectively remove non-cell particles from an image, which may lead to erroneous counting and classifying of cells and platelets.
Claim 11 is rejected as being unpatentable over Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad in view of Tai et al. (“Blood Cell Image Classification Based on Hierarchical SVM”, Year: 2011, DOI: 10.1109/ISM.2011.29; hereinafter “Tai”).
Regarding Claim 11, Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad teaches the method according to claim 1, wherein the classification of identified masks representing (C. Overlapping Cervical Cell Segmentation Based on Gradient Thresholding, Edge and Region Integration, Tareef discloses identifying overlapping cells, which is based on both circularity and area.)
Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad does not teach classifying masks representing white cells and platelets using a measure of circularity and mask area.
Tai discloses classifying masks representing white cells and platelets using a measure of circularity and mask area (C. Feature Extraction, Tai discloses extracting features from an image, including area and circularity, as a way to classify leukocytes and thrombocytes.).
Meimban, Salahat, Arteta, Tareef, Shahzad, and Tai are considered to be analogous to the claimed invention as they are in the same field of analyzing biological/physiological images. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad such that the classification of white cells and platelets was performed using the methods disclosed by Tai. The motivation for this combination being the ability to automate the process of classifying white cells and platelets.
Claim 12 is rejected as being unpatentable over Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad in view of Tai in view of Wang (CN 103020639; hereinafter “Wang”).
Regarding Claim 12, Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad in view of Tai teaches the method according to claim 11.
Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad in view of Tai does not teach wherein when the circularity of a blood constituent in step [iv.] is greater than 0.9, it is classified as a white blood cell.
Wang discloses wherein when the circularity of a blood constituent in step [iv.] is greater than 0.9, it is classified as a white blood cell (Page 7, Wang discloses that lymphocytes have a circularity close to 1.).
Meimban, Salahat, Arteta, Tareef, Shahzad, Tai, and Wang are considered to be analogous to the claimed invention as they are in the same field of analyzing biological/physiological images. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Meimban in view of Salahat in view of Arteta in view of Tareef in view of Shahzad in view of Tai such that the filtering and selection of white blood cells used the circularity threshold greater than 0.9, as disclosed by Wang. The motivation for this combination being the ability to use an established threshold which has been shown to be able to detect white blood cells.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PROMOTTO TAJRIAN ISLAM whose telephone number is (703)756-5584. The examiner can normally be reached Monday - Friday 8:30 am - 5:00 pm EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Chan Park can be reached at (571) 272-7409. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/PROMOTTO TAJRIAN ISLAM/
Examiner, Art Unit 2669 /CHAN S PARK/Supervisory Patent Examiner, Art Unit 2669