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 Arguments
Applicant’s arguments, see applicant’s correspondence filed 8/24/2026 with respect to the rejection(s) of claim(s) 1-15 under 35 U.S.C. 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Matlab 7.
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.
Claim(s) 1, 3-9, 11, 12 and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over
Loken et al. (US 2006/0263833 A1) in view of
Bolstad (Bolstad, Paul, “GIS Fundamentals: A First Text on Geographic Information Systems”, Fourth Edition, Eider Press, MN, 2012, pp. 503-508) and
Kirchanski et al. (US 4,882,284 A) and in further view of
Matlab 7 (“Matlab 7: Getting Started Guide”, MathWorks, Sixteenth printing September 2010).
Regarding claim 1, Loken discloses:
A specimen analysis device for analyzing a specimen containing formed components, the specimen (Loken, Abstract: system for diagnosing a test of biological cells, i.e. “formed components”; also see Fig. 1 and ¶75) analysis device comprising:
(Loken, ¶9: exposing a cell to plurality of reagents; ¶39 discusses specimen for introduction into a flow cytometer; e.g. ¶94 discusses 4-color analysis of cells placed in a tube and stained with reagents);
a light source configured to apply irradiating light to the measurement sample (Lokens, ¶40: flow cytometer analyzing cells based on light scattering properties of each cell; ¶41: instruments currently available in the art are configured with ultraviolet-emitting sources, such as the four-laser, 10-color Becton Dickinson LSR II);
a detector controlled to receive generated light from the formed components in the measurement sample (Lokens, ¶40: fluorescence detection using photomultiplier tubes and detectors to obtain light scattering properties of sample, including flow cytometry can routinely detect multiple immunofluorescent markers in a quantitative manner and can measure other parameters such as forward light scatter (which is an indication of cell size) and right angle light scatter (which is an indication of cell granularity));
a controller programmed to create, based on measurement values of at least three parameters obtained from detection signal generated from the light received by the detector, (Loken, Fig. 1 and ¶76: measurement system 102 measures characteristics of cells in a sample of cells; ¶78: diagnostic system 104 including controller 110; Also, ¶80 discussing system implemented as digital signal processor or controller executing instructions in memory)
(1) a three-dimensional distribution having three axes corresponding to three parameters, wherein each of the formed components is plotted by a dot at a coordinate in the three-dimensional distribution according to the measurement values of the three parameters, (Loken, ¶10: mapping each cell in a normal set of biological cells to a corresponding point in an n-dimensional space using a first protocol; ¶99 discloses 6 dimensional data (4 color and 2 light scatter parameters) for display; ¶101: The data is displayed by a diagnostic system, such as the diagnostic system 104 illustrated in FIG. 1, in a rotatable pseudo three-dimensional graphic display with color-coding based on cluster identification; ¶103: The graphic representation 402 comprises an x-axis 406 corresponding to a fluorescence intensity for CD20, a y-axis 408 corresponding to a fluorescence intensity for CD10, and a z-axis 410 corresponding to a fluorescence intensity for CD45 – see Fig. 10A) and
(2) a(Loken, Fig. 9B discloses clusters split into distributions, e.g. Stage III vs Stage IV having a height, along two axes representing 2 of the 3 parameters, e.g. CD 10 and CD 20; ¶¶98-99 discusses the plotting of data set from the 6 dimensional data of parameters, including in Cartesian coordinate system with horizontal axis and vertical axes corresponding to parameters; ¶101 further discusses clustering of cell data, see e.g. Fig. 9B, where the “distribution of plots” or clusters are represented in 2D, including a height, i.e. visual representation; Also note that ¶38 discloses that the cell markers are CD cell surface markers); and
a display that displays the three-dimensional distribution and the (Loken, ¶24: FIGS. 4A to 9A and 4B to 9B are illustrations of multi-dimensional data projected into pseudo two-dimensional displays generated by a system; ¶25: FIGS. 10A and 10B are illustrations of multi-dimensional data projected into pseudo three-dimensional displays generated by a system, such as the system illustrated in FIG. 1; ¶98: The populations of interest can also be displayed in other ways, such as corresponding four-shade analysis displays, which are illustrated in FIG. 4B to 9B; ¶102: diagnostic system displays data in three-axis coordinate system – Figs. 10A and 10B; ¶179: diagnostic system displays on a suitable display device)
Loken does not explicitly disclose the second plot as the particular type of plot, or surface plot as claimed. Conversion of a 2D data set into a 3D surface plot representing distribution of data points, however, is a well-known technique for statistical analysis of data. Bolstad discloses:
a surface plot corresponding to two parameters out of the three parameters, wherein each of the formed components is plotted at a coordinate in the surface plot according to the measurement values of the two parameters and a distribution of plots is represented by a height (Bolstad, p. 503: Kernal Mapping, ¶1: “Kernal mapping uses a set of sample locations to estimate a continuous density surface”; ¶2: “Kernal is based on a density distribution that is assumed for each sample point”; ¶3 discloses example of density defects in tile floor, counting the number of defects per tile; ¶506: right column: “Kernal mapping is generally a three-step process…” which discusses the collection of samples at coordinate locations, and choosing a density function, summarized by the equation λ(x,y), which is a composite density distribution; p. 507, Figure 12-28b discloses using kernels to map density distributions across a two-dimensional surface, where all sample points are plotted – e.g. density of occurrence of the underlying variable for a 2D data set, in this case the number of points at values x-coordinate and y-coordinate for tile floor, the density of defects per coordinate space)
Both Loken and Bolstad are directed to computer graphic interfaces for presenting gathered data sets within different graphical representations for presenting and analyzing data in graphical form on a computer device. It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable expectation of success, to modify the graphical user interface for presenting specimen data within 2D and 3D coordinate space as provided by Loken, utilizing the conversation of 2D data to a 3D surface plot for presenting distribution data as provided by Bolstad, using known electronic interfacing and programming techniques. The modification merely substitutes one known type of graphical representation of data for another, yielding predictable results of presenting data in a different mathematical arrangement for statistical analysis (namely substituting the 2D charts for presenting data points in 2D for a 3D distribution graph of the same data points, but including a mathematical calculation of the distribution for viewing data differently). Moreover, the modification improves upon the graphical display of data as presented by Loken by allowing for a different mathematical perspective of the data for easier understanding and analysis by presenting a different view of the distribution of data points that assists with understanding the represented data.
Loken does not explicitly disclose the particular components of the device having a “flow cell” (wherein a flow cell to flow therein a measured sample prepared from the specimen and a reagent). The use of a flow cell for cell cytometry is well known.
Kirchanski discloses:
A specimen analysis device for analyzing a specimen containing formed components, the specimen analysis device comprising: a flow cell to flow therein a measured sample prepared from the specimen and a reagent and a light source configured to apply irradiating light to the measurement sample in the flow cell (Kirchanski, [13:33-56]: solution of dye composition stained blood cells “pumped into a flow cell where blood cells were passed single file through a red laser beam” and light scatter and fluorescence measurements were made on individual cells)
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable expectation of success, to modify the system and method for cytometry measuring light parameters of a cell sample to perform flow cytometry as provided by Loken, utilizing the conversation of 2D data to a 3D surface plot for presenting distribution data as provided by Bolstad, to incorporate the flow cell equipment for arranging cells for light parameter measurements in flow cytometry as provided by Kirchanski, using known engineering techniques. The modification results in an improved flow cytometry by arranging cells in a pattern for better analysis (i.e. single file for performing measurements on a sample) to ensure more accurate test results (i.e. not obfuscating cells during sensor readings or conflating results).
Loken, modified by Bolstad and Kirchanski teach all the recited elements of graphing a set of data related to specimen analysis as claimed, including displaying different charts for the same data sets as discussed above. The only element missing is the particular feature of allowing the hiding a dot in a second plot in response to hiding a specific dot in the first plot. This ability to coordinate data points across plots that share the same data, however, was known at the time of effective filing.
MatLab 7 discloses:
In response to hiding a specific dot in the [first] distribution, hiding a dot in the [second] plot corresponding to the specific dot (Matlab 7, pages 5-19 to 5-21 discloses a user interface that allows a user to select displayed points and delete them;
In particular, last paragraph of 5-20 states, “Data brushing is a related feature that lets you highlight one or more observations on a graph by clicking or dragging”, and 5-19 states that “After you brush data observations, you can perform the following operations on them: Delete them”;
Page 5-22 to 5-23, “Linked plots, or data linking, is a feature closely related to data brushing. A plot is said to be linked when it has a live connection to the workspace data it depicts. The copies of variables stored in a plot object’s XData, YData, (and, where appropriate, ZData), automatically updated whenever the workspace variables to which they are linked change or are deleted. This causes the graphs on which they appear to update automatically”;
Also, see 5-23, stating: “Linking plots to variables lets you track specific observations through different presentations of them. When you brush data points in linked plots, brushing one graph highlights the same observations in every graph that is linked to the same variables.”)
In other words, the combination of the technique of performing one operation on a first graph that is propagated to the underlying data and therefore to all linked graphs, as taught by MatLab 7, along with the coordinated graphs of the particular data as provided by Loken, Bolstad and Kirchanski, teaches the limitation of the claim (i.e. wherein in response to hiding a specific dot in the three-dimensional distribution, hiding a dot in the surface plot corresponding to the specific dot.)
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable expectation of success, to modify the system and method for cytometry measuring light parameters of a cell sample to perform flow cytometry as provided by Loken, utilizing the conversation of 2D data to a 3D surface plot for presenting distribution data as provided by Bolstad, and incorporating the flow cell equipment for arranging cells for light parameter measurements in flow cytometry as provided by Kirchanski, by further utilizing the graphing technique of coordinating multiple graphs to a single user control as provided by Matlab 7, using known engineering techniques. The modification results in an improved graphical user interface for displaying data for analysis by allowing user greater control over the presented data and automating edits to multiple graphs to allow for easier usability.
Regarding claim 3, Loken further discloses:
wherein the display hides specific dots on the three-dimensional distribution or changes a display format of the specific dots according to an operation performed by a user (Loken, ¶104: user can update information used to generate the display 400 using data entry fields, such as 432 and 434 in Fig. 10B, which are re-clustering and threshold value settings, as well as Fig. 10B having user interface element for “Hide Clusters”; ¶105: menu of GUI allowing selection for different stored filtering parameters, including excluding data)
Regarding claim 4, Loken further discloses:
wherein the controller is programmed to classify the formed components on the basis of the measurement values (Loken, ¶¶99-101: clusters identified by projections of 6 dimensional data, including color and light scatter parameters, and further cluster stage identified using fluorescence intensity levels – Figs. 4-9 discloses the clustering of a plurality of parameters shown along the axes, along with a plurality of classifications such as different stages. e.g. fig 8A, based on clusters -i.e. formed components; Figs. 10A and 10B and ¶102 discloses the data set clustering within three dimensions; also ¶103: clustering assigned according to maturation level; also note ¶132: wavelet clustering)
Regarding claim 5, Loken further discloses:
Wherein the display receives selection types of formed components from among the classified formed components and hides specific dots or changes a display format of the specific dots for each of the types of the formed components having been selected (Loken, Figs. 10A-10B, button “Hide Clusters”, ¶105: permit user selection including selecting filter parameters, such as “exclude data with a side scatter parameter corresponding to more than 102 and CD19 parameter corresponding to less than” a threshold, as well as allowing selection of a specific cluster on which to apply various filter criteria; Also, ¶¶100-103 discloses user identifying clusters in displayed data and assessing cells assigned to initial clusters, and assigning color to clusters for display in Figs. 10A and 10B)
Regarding claim 6, Loken further discloses:
wherein the display receives selection of the dots to be displayed on the three-dimensional distribution and displays the dots having been selected (Loken, Figs. 10A and 10B, “Hide Clusters” and “Unhide Clusters”; ¶105: permit user selection including selecting filter parameters, such as “exclude data with a side scatter parameter corresponding to more than 102 and CD19 parameter corresponding to less than” a threshold, as well as allowing selection of a specific cluster on which to apply various filter criteria – not that selection of a range indicates both points to show and points to hide for display, depending on the range they fall into)
Regarding claim 7, Loken further discloses:
Wherein the display receives selection of the specific dots to be hidden on the three-dimensional distribution and hides the specific dots having been selected (Loken, Figs. 10A and 10B, “Hide Clusters” and “Unhide Clusters”; ¶105: permit user selection including selecting filter parameters, such as “exclude data with a side scatter parameter corresponding to more than 102 and CD19 parameter corresponding to less than” a threshold, as well as allowing selection of a specific cluster on which to apply various filter criteria – not that selection of a range indicates both points to show and points to hide for display, depending on the range they fall into)
Regarding claim 8, Loken further discloses:
Wherein the display receives selection of the specific dots to be displayed on the three-dimensional distribution with the display format changed and displays the specific dots on the three dimensional distribution with the display format changed, in response to an operation of changing the display format of the specific dots having been selected (Loken, Figs. 10A and 10B, “Hide Clusters” and “Unhide Clusters” and “Show Boundary”; ¶105: permit user selection including selecting filter parameters, such as “exclude data with a side scatter parameter corresponding to more than 102 and CD19 parameter corresponding to less than” a threshold, as well as allowing selection of a specific cluster on which to apply various filter criteria – not that selection of a range indicates both points to show and points to hide for display, depending on the range they fall into; Also, ¶¶100-103 discloses user identifying clusters in displayed data and assessing cells assigned to initial clusters, and assigning color to clusters for display in Figs. 10A and 10B)
Regarding claim 9, Loken further discloses:
Further comprising a storage configured to store, for each formed component, the measurement values, information for identifying the dots, and information regarding display/hiding of the specific dots in association with each other, wherein the display hides the specific dots on the three-dimensional distribution or changes the display format of the specific dots on the basis of the information regarding display/hiding of the specific dots in storage. (Loken, ¶95: An example data structure 200 for storing a data set is illustrated in FIG. 2. With reference to FIGS. 1 and 2, the parser 114 parsed the header section 202, text section 204, data section 206 and analysis section 208 and collected information, including a parameter name, a total number of data points and data type details; ¶96 further discloses properties file with header of how to parse loaded data structure; ¶104 further discloses tabular representation of data, including percentage of points and thresholding data; ¶105: For example, menu selections may be included for: selecting between different stored filtering parameters, and where filter parameters includes “exclude data with a side scatter parameter corresponding to more than 102 and CD19 parameter corresponding to less than” a threshold, as well as allowing selection of a specific cluster on which to apply various filter criteria – not that selection of a range indicates both points to show and points to hide for display, depending on the range they fall into)
Regarding claim 11, Loken further discloses:
Wherein the display displays the surface plot using two parameters out of the three parameters used as three axes of the three-dimensional distribution (Loken, Fig. 9B discloses clusters split into distributions, e.g. Stage III vs Stage IV having a height, along two axes representing 2 of the 3 parameters, e.g. CD 10 and CD 20; ¶¶98-99 discusses the plotting of data set from the 6 dimensional data of parameters, including in Cartesian coordinate system with horizontal axis and vertical axes corresponding to parameters; ¶101 further discusses clustering of cell data, see e.g. Fig. 9B, where the “distribution of plots” or clusters are represented in 2D, including a height, i.e. visual representation; Also note that ¶38 discloses that the cell markers are CD cell surface markers)
Regarding claim 12, Loken further discloses:
Wherein the display displays a plurality of (Loken, Figures 4A-9B discloses plurality of plots representing included in the 3D plot, e.g. CD 10, CD 20, and CD 45; ¶¶98-99 discusses the plotting of data set from the 6 dimensional data of parameters, including in Cartesian coordinate system with horizontal axis and vertical axes corresponding to parameters; Also note that ¶38 discloses that the cell markers are CD cell surface markers)
Bolstad discloses a surface plot on basis of the parameters (Bolstad, p. 503: Kernal Mapping, ¶1: “Kernal mapping uses a set of sample locations to estimate a continuous density surface”; ¶2: “Kernal is based on a density distribution that is assumed for each sample point”; ¶3 discloses example of density defects in tile floor, counting the number of defects per tile; ¶506: right column: “Kernal mapping is generally a three-step process…” which discusses the collection of samples at coordinate locations, and choosing a density function, summarized by the equation λ(x,y), which is a composite density distribution; p. 507, Figure 12-28b discloses using kernels to map density distributions across a two-dimensional surface, where all sample points are plotted – e.g. density of occurrence of the underlying variable for a 2D data set, in this case the number of points at values x-coordinate and y-coordinate for tile floor, the density of defects per coordinate space)
Both Loken and Bolstad are directed to computer graphic interfaces for presenting gathered data sets within different graphical representations for presenting and analyzing data in graphical form on a computer device. It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable expectation of success, to modify the graphical user interface for presenting specimen data within 2D and 3D coordinate space as provided by Loken, utilizing the conversation of 2D data to a 3D surface plot for presenting distribution data as provided by Bolstad, using known electronic interfacing and programming techniques. The modification merely substitutes one known type of graphical representation of data for another, yielding predictable results of presenting data in a different mathematical arrangement for statistical analysis (namely substituting the 2D charts for presenting data points in 2D for a 3D distribution graph of the same data points, but including a mathematical calculation of the distribution for viewing data differently). Moreover, the modification improves upon the graphical display of data as presented by Loken by allowing for a different mathematical perspective of the data for easier understanding and analysis by presenting a different view of the distribution of data points that assists with understanding the represented data.
Regarding claim 15, Loken further discloses:
a signal processing circuit configured to obtain the measurement values of the at least three parameters from the detection signal (Loken, ¶¶40-41: flow cytometry detecting multiple immunofluorescent markers to generate six dimensional data; Fig. 1 and ¶76: measurement system 102 measures characteristics of cells in a sample of cells; ¶77: measurement system comprising controllers, memories, circuitry and hardware; ¶99 further disclosing the 6 dimensions as related to detected parameters)
Claim(s) 2 and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over
Loken et al. (US 2006/0263833 A1) in view of
Bolstad (Bolstad, Paul, “GIS Fundamentals: A First Text on Geographic Information Systems”, Fourth Edition, Eider Press, MN, 2012, pp. 503-508),
Kirchanski et al. (US 4,882,284 A) and
Matlab 7 (“Matlab 7: Getting Started Guide”, MathWorks, Sixteenth printing September 2010) and in further view of
Miyamoto (US 2006/0004541 A1).
Regarding claim 2, the limitations included from claim 1 are rejected based on the same rationale as claim 1 set forth above. Further regarding claim 2, Miyamoto discloses:
wherein the display displays the surface plot in an area which is different from an area where the three-dimensional distribution is displayed (Fig. 16 and ¶¶135-137 discloses screen displaying both 2D chart and three dimensional chart on same screen but different areas; Also see ¶147)
Both Loken and Miyamoto are directed to graphical user interfaces for analyzing specimen data. Furthermore, it would have been obvious to one of ordinary skill in the art, before the effective filing date and with a reasonable expectation of success, to modify the graphical user interface for presenting specimen data in 2D and 3D graph form as provided by Loken, utilizing the conversation of 2D data to a 3D surface plot for presenting distribution data as provided by Bolstad, incorporating the flow cell equipment for arranging cells for light parameter measurements in flow cytometry as provided by Kirchanski, and utilizing the graphing technique of coordinating multiple graphs to a single user control as provided by Matlab 7, by further using multiple windows for display of data on the interface window as provided by Miyamoto, using known electronic interfacing and programming techniques. The modification results in an improved user interface by allowing different perspectives of the data for clearer analysis and understanding by a viewer (see e.g. Miyamoto, ¶138 discussing how providing additional scatter diagrams make it easier to identify information.)
Regarding claim 13, the limitations included from claim 1 are rejected based on the same rationale as claim 1 set forth above. Further regarding claim 13, Loken modified by Bolstad further discloses using a surface plot (Bolstad, p. 503: Kernal Mapping, ¶1: “Kernal mapping uses a set of sample locations to estimate a continuous density surface”; ¶2: “Kernal is based on a density distribution that is assumed for each sample point”; ¶3 discloses example of density defects in tile floor, counting the number of defects per tile; ¶506: right column: “Kernal mapping is generally a three-step process…” which discusses the collection of samples at coordinate locations, and choosing a density function, summarized by the equation λ(x,y), which is a composite density distribution; p. 507, Figure 12-28b discloses using kernels to map density distributions across a two-dimensional surface, where all sample points are plotted – e.g. density of occurrence of the underlying variable for a 2D data set, in this case the number of points at values x-coordinate and y-coordinate for tile floor, the density of defects per coordinate space)
Both Loken and Bolstad are directed to computer graphic interfaces for presenting gathered data sets within different graphical representations for presenting and analyzing data in graphical form on a computer device. It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable expectation of success, to modify the graphical user interface for presenting specimen data within 2D and 3D coordinate space as provided by Loken, utilizing the conversation of 2D data to a 3D surface plot for presenting distribution data as provided by Bolstad, using known electronic interfacing and programming techniques. The modification merely substitutes one known type of graphical representation of data for another, yielding predictable results of presenting data in a different mathematical arrangement for statistical analysis (namely substituting the 2D charts for presenting data points in 2D for a 3D distribution graph of the same data points, but including a mathematical calculation of the distribution for viewing data differently). Moreover, the modification improves upon the graphical display of data as presented by Loken by allowing for a different mathematical perspective of the data for easier understanding and analysis by presenting a different view of the distribution of data points that assists with understanding the represented data.
Miyamoto discloses:
Wherein the display hides the specific dots or changes the display format in the second plot in response to hiding the specific dots or changing the display format in the three-dimensional distribution (Miyamoto, Figs. 6-7 and ¶89: user selection of an area of scatter diagram 61; ¶94: acquire coordinate information of selected polygonal area; Fig. 16 and ¶136: polygonal areas 71a and 71b set on 3D diagram using same method as in 2D embodiment, determining a 3D space as a fraction area; ¶137: Symbols 72a to 74a indicate scatter diagrams that are obtained by projecting only the selected fraction area (area A) onto the X1-Y plane, X2-Y plane and X1-X2 plane; ¶138: the user determines whether or not the distribution of blood corpuscles belonging to area A is appropriate by viewing the scatter diagrams 72a to 74a, and if it is inappropriate, the fraction area in the three-dimensional distribution chart 71 is changed; thus, it becomes possible to easily set an appropriate fraction area; ¶141: “The explanation has been given by exemplifying a case in which area A is selected; however, in the case when another area is selected, the scatter diagrams and histograms relating to tangible components belonging to the corresponding area are drawn”)
Both Loken and Miyamoto are directed to graphical user interfaces for analyzing specimen data. Furthermore, it would have been obvious to one of ordinary skill in the art, before the effective filing date and with a reasonable expectation of success, to modify the graphical user interface for presenting specimen data in 2D and 3D graph form as provided by Loken, utilizing the conversation of 2D data to a 3D surface plot for presenting distribution data as provided by Bolstad, and incorporating the flow cell equipment for arranging cells for light parameter measurements in flow cytometry as provided by Kirchanski, utilizing the graphing technique of coordinating multiple graphs to a single user control as provided by Matlab 7, by utilizing the technique of displaying the specimen data in 2D and 3D on the interface window based on user input for selected data as provided by Miyamoto, using known electronic interfacing and programming techniques. The modification results in an improved user interface by allowing different perspectives of the data for clearer analysis and understanding by a viewer (see e.g. Miyamoto, ¶138 discussing how providing additional scatter diagrams make it easier to identify information), and allowing greater control of the displayed data to the user.
Claim(s) 10 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over
Loken et al. (US 2006/0263833 A1) in view of
Bolstad (Bolstad, Paul, “GIS Fundamentals: A First Text on Geographic Information Systems”, Fourth Edition, Eider Press, MN, 2012, pp. 503-508),
Kirchanski et al. (US 4,882,284 A) and
Matlab 7 (“Matlab 7: Getting Started Guide”, MathWorks, Sixteenth printing September 2010) and in further view of
Posch (Posch, Maya, “On The Coordinate System Of QGraphicsScene In Qt”, Maya’s Programming and Electronics Blog, published Dec. 17, 2012 at https://mayaposch.wordpress.com/2012/12/17/on-the-coordinate-system-of-qgraphicsscene-in-qt/, archived at archive.org as of Jan. 13, 2014 – IDS provided reference).
Regarding claim 10, the limitations included from claim 1 are rejected based on the same rationale as claim 1 set forth above. Further regarding claim 10, Loken further discloses:
Wherein the display displays the three-dimensional distribution using three (Loken, Figs. 10A and 11A show parameter names set to each axis on display)
Loken modified by Kirchanski fails to explicitly teach the use of color coding as claimed.
Posch discloses:
Wherein the display displays the three-dimensional chart using three color-coded axes and displays a parameter name corresponding to a color of each axis (Posch discloses first two images having color coded axes corresponding between the 2D and 3D axes for the same parameter, x vs. y:
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It would have been obvious to one of ordinary skill in the art, before the effective filing date and with a reasonable expectation of success, to modify the graphical user interface for presenting specimen data in 2D and 3D graph form as provided by Loken, utilizing the conversation of 2D data to a 3D surface plot for presenting distribution data as provided by Bolstad, incorporating the flow cell equipment for arranging cells for light parameter measurements in flow cytometry as provided by Kirchanski, and utilizing the graphing technique of coordinating multiple graphs to a single user control as provided by Matlab 7, by further including corresponding colored axes between 2D and 3D coordinate space as provided by Posch, using known electronic interfacing and programming techniques. The modification results in an improved user interface presenting different graph perspectives by coordinating axes colors for easier user understanding of which axes correspond between charts.
Regarding claim 14, the limitations included from claim 1 are rejected based on the same rationale as claim 1 set forth above. Further regarding claim 14, Loken further discloses:
The display displays the three-dimensional distribution and the surface plot such that the three axes used in the three-dimensional distribution and two axes corresponding to the two parameters used in the second plot are corresponding, and the axes of the same parameter are given the same identifier between the three-dimensional distribution and the second plot (Loken, Fig. 9B discloses clusters split into distributions, e.g. Stage III vs Stage IV having a height, along two axes representing 2 of the 3 parameters, e.g. CD 10 and CD 20; ¶¶98-99 discusses the plotting of data set from the 6 dimensional data of parameters, including in Cartesian coordinate system with horizontal axis and vertical axes corresponding to parameters)
Bolstad discloses a surface plot from the parameters (Bolstad, p. 503: Kernal Mapping, ¶1: “Kernal mapping uses a set of sample locations to estimate a continuous density surface”; ¶2: “Kernal is based on a density distribution that is assumed for each sample point”; ¶3 discloses example of density defects in tile floor, counting the number of defects per tile; ¶506: right column: “Kernal mapping is generally a three-step process…” which discusses the collection of samples at coordinate locations, and choosing a density function, summarized by the equation λ(x,y), which is a composite density distribution; p. 507, Figure 12-28b discloses using kernels to map density distributions across a two-dimensional surface, where all sample points are plotted – e.g. density of occurrence of the underlying variable for a 2D data set, in this case the number of points at values x-coordinate and y-coordinate for tile floor, the density of defects per coordinate space)
Both Loken and Bolstad are directed to computer graphic interfaces for presenting gathered data sets within different graphical representations for presenting and analyzing data in graphical form on a computer device. It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention and with a reasonable expectation of success, to modify the graphical user interface for presenting specimen data within 2D and 3D coordinate space as provided by Loken, utilizing the conversation of 2D data to a 3D surface plot for presenting distribution data as provided by Bolstad, using known electronic interfacing and programming techniques. The modification merely substitutes one known type of graphical representation of data for another, yielding predictable results of presenting data in a different mathematical arrangement for statistical analysis (namely substituting the 2D charts for presenting data points in 2D for a 3D distribution graph of the same data points, but including a mathematical calculation of the distribution for viewing data differently). Moreover, the modification improves upon the graphical display of data as presented by Loken by allowing for a different mathematical perspective of the data for easier understanding and analysis by presenting a different view of the distribution of data points that assists with understanding the represented data.
The only limitation not taught by Loken modified by Bolstad and Kirshchanski is that the axes of the two plots are color coded the same.
Posch discloses:
The display displays the three-dimensional graph and the second plot such that the three axes used in the three-dimensional graph and two axes corresponding to the two parameters used in the second plot are color-coded, and the axes of the same parameter are given the same color between the three-dimensional graph and the second plot (Posch discloses first two images having color coded axes corresponding between the 2D and 3D axes for the same parameter, x (red) vs. y (blue) in both graphs:
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It would have been obvious to one of ordinary skill in the art, before the effective filing date and with a reasonable expectation of success, to modify the graphical user interface for presenting specimen data in 2D and 3D graph form as provided by Loken, utilizing the conversation of 2D data to a 3D surface plot for presenting distribution data as provided by Bolstad, incorporating the flow cell equipment for arranging cells for light parameter measurements in flow cytometry as provided by Kirchanski, utilizing the graphing technique of coordinating multiple graphs to a single user control as provided by Matlab 7, and by further including corresponding colored axes between 2D and 3D coordinate space as provided by Posch, using known electronic interfacing and programming techniques. The modification results in an improved user interface presenting different graph perspectives by coordinating axes colors for easier user understanding of which axes correspond between charts.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WILLIAM A BEUTEL whose telephone number is (571)272-3132. The examiner can normally be reached Monday-Friday 9:00 AM - 5:00 PM (EST).
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/WILLIAM A BEUTEL/Primary Examiner, Art Unit 2616
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