SYSTEMS AND METHODS FOR IDENTIFYING GROUPINGS OF CELLS

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 . DETAILED ACTION Claims 1 – 20 are pending in this application. Claims 1, 12 and 16 are independent. Claim Rejections - 35 USC § 102 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention. (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. Claim(s) 1 – 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by ROGNIN, Nicolas (US-20220120664-A1, hereinafter simply referred to as Nicolas). Regarding independent claim(s) 1 and 12, Nicolas teaches: A method (e.g., FIG. 2 of Nicolas), executed by an electronic processing device, for an image processing system (e.g., FIG. 1 of Nicolas), the method comprising: receiving an image, captured by an imaging device, of a sample having a plurality of cells (See at least Nicolas, ¶ [0079–0080]; FIGS. 1–4, 6–8), wherein the image includes labeling data (e.g., cell location, count, live/dead determination of Nicolas) for each of the plurality of cells (See at least Nicolas, ¶ [0135, 0149]; FIGS. 1–4, 6–8); applying filters (e.g., low pass filtering of Nicolas), determined based on the labeling data, to the image (See at least Nicolas, ¶ [0129, 0132–0133, 0135]; FIGS. 1–4, 6–8); processing the image to identify a plurality of groupings of the plurality of cells (See at least Nicolas, ¶ [0162]; FIGS. 1–4, 6–8), wherein each respective grouping of the plurality of groupings includes at least two cells having a same viability whose cell membranes are touching (e.g., FIGS. 14, 15A & 15C of Nicolas) at least one other cell in the respective grouping (See at least Nicolas, ¶ [0033, 0164, 0168]; FIGS. 1–4, 6–8); and fitting an ellipse around each of the groupings by determining ellipse data for each of the ellipses (See at least Nicolas, ¶ [0164, 0166]; FIGS. 1–4, 6–8). Regarding independent claim 16, Nicolas teaches: A method (e.g., FIG. 2 of Nicolas), executed by an electronic processing device, for an image processing system (e.g., FIG. 1 of Nicolas), the method comprising: receiving an image, captured by an imaging device, of a sample having a plurality of cells (See at least Nicolas, ¶ [0079–0080]; FIGS. 1–4, 6–8), receiving cell boundary information for the image (See at least Nicolas, ¶ [0129, 0132–0133, 0135]; FIGS. 1–4, 6–8); generating a binary mask of the image based on the cell boundary information (See at least Nicolas, ¶ [0030, 0093–0095]; FIGS. 1–4, 6–8); running a connected component analysis on the binary mask to detect connected components (See at least Nicolas, ¶ [0093–0095]; FIGS. 1–4, 6–8); generating cell aggregate data based on the image and the detected connected components (See at least Nicolas, ¶ [0030, 0093–0095, 0162]; FIGS. 1–4, 6–8); and providing the cell aggregate data via a display (See at least Nicolas, ¶ [0164, 0166]; FIGS. 1–4, 6–8). Regarding dependent claim 2, Nicolas teaches: wherein the ellipse data includes a center coordinate, a radius major, a radius minor, and an orientation (See at least Nicolas, ¶ [0164, 0166]; FIGS. 1–4, 6–8). Regarding dependent claim 3, Nicolas teaches: wherein the labeling data include a location and a viability of each of the plurality of cells (See at least Nicolas, ¶ [0135, 0149]; FIGS. 1–4, 6–8). Regarding dependent claim 4, Nicolas teaches: wherein the plurality of cells is depicted in a foreground of the image (See at least Nicolas, ¶ [0128–0130]; FIGS. 1–4, 6–8). Regarding dependent claims 5 and 13, Nicolas teaches: wherein applying the filters to the image includes: determining a foreground histogram of foreground pixels in the image and a background histogram of background pixels in the image (See at least Nicolas, ¶ [0164]; FIGS. 1–4, 6–8); normalizing the foreground histogram and the background histogram into an empirical probability density function (See at least Nicolas, ¶ [0164]; FIGS. 1–4, 6–8); and applying a morphology operation to erode the image (See at least Nicolas, ¶ [0094]; FIGS. 1–4, 6–8). Regarding dependent claims 6 and 14, Nicolas teaches: wherein the image includes a plurality of pixels, wherein applying the filters to the image further includes: for each respective pixel of the plurality of pixels whose values changed during erosion of the image (See at least Nicolas, ¶ [0162–0163]; FIGS. 1–4, 6–8), determining a likelihood that the respective pixel is a part of a foreground of the image (See at least Nicolas, ¶ [0162–0163]; FIGS. 1–4, 6–8), and restoring each respective pixel based on the respective likelihood satisfying a threshold (See at least Nicolas, ¶ [0162–0163, 0164]; FIGS. 1–4, 6–8). Regarding dependent claim 7, Nicolas teaches: wherein the threshold is greater than 90 percent (See at least Nicolas, ¶ [0030]; FIGS. 1–4, 6–8). Regarding dependent claims 8 and 15, Nicolas teaches: wherein the plurality of groupings of cells are identified by traversing a plurality of pixels in the image associated with each of the plurality of cells to determine connected points in a two-dimensional (2D) space represented in the image (See at least Nicolas, ¶ [0092]; FIGS. 1–4, 6–8). Regarding dependent claim 9, Nicolas teaches: where the connected points are extracted from an equivalence table dictionary to determine connected cells in each of the plurality of groupings (See at least Nicolas, ¶ [0092, 0107, 0113]; FIGS. 1–4, 6–8). Regarding dependent claim 10, Nicolas teaches: providing the image and the ellipse data to a display (See at least Nicolas, ¶ [0164, 0166]; FIGS. 1–4, 6–8). Regarding dependent claim 11, Nicolas teaches: determining a total number of the plurality of cells and a percentage of the plurality of cells included in the plurality of groupings (See at least Nicolas, ¶ [0158–0159]; FIGS. 1–4, 6–8). Regarding dependent claim 17, Nicolas teaches: wherein the binary mask sets each pixel in the image to a first value in response to the pixel representing a cell boundary and a second value in response to the pixel not representing a cell boundary (See at least Nicolas, ¶ [0094–0095]; FIGS. 1–4, 6–8). Regarding dependent claim 18, Nicolas teaches: wherein the connected component analysis performs 8-connectivity detection (See at least Nicolas, ¶ [0092, 0096]; FIGS. 1–4, 6–8). Regarding dependent claim 19, Nicolas teaches: wherein the cell of the plurality of cells represents at least one selected from a group consisting of a number of all cells in the image, a number of live cells in the image, and a number of dead cells in the image (See at least Nicolas, ¶ [0149, 0152]; FIGS. 1–4, 6–8). Regarding dependent claim 20, Nicolas teaches: wherein the aggregate cell data includes at least one selected from a group consisting of an aggregate fraction of all cells in the image, an aggregate fraction of live cells in the image, and an aggregate fraction of dead cells in the image (See at least Nicolas, ¶ [0149, 0152, 0158–0159]; FIGS. 1–4, 6–8). Conclusion The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure: See the Notice of References Cited (PTO–892) Any inquiry concerning this communication or earlier communications from the examiner should be directed to IDOWU O OSIFADE whose telephone number is (571)272-0864. The Examiner can normally be reached on Monday-Friday 8:00am-5:00pm EST. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the Examiner’s Supervisor, JOHN M. VILLECCO can be reached on (571) 272 – 7319. The fax phone number for the organization where this application or proceeding is assigned is (571) 273 – 8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at (866) 217 – 9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call (800) 786 – 9199 (IN USA OR CANADA) or (571) 272 – 1000. /IDOWU O OSIFADE/Primary Examiner, Art Unit 2675