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 .
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 (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 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)(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) 1-5, 7-17, 33, 46, and 48 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Teramoto et al., US 2024/0152692.
Regarding claim 1, Teramoto discloses a method (fig. 12; para 0111; an information processing method) comprising:
loading a point cloud, each point within the point cloud representing a feature of a biological sample at its corresponding location (para 0069, 0072, and 0078; generate the annotation data 802 from a pathological image based on the pathological image (image data) of a biological specimen; For example, the annotation data 802 may be point cloud coordinate data including coordinates of a fine point cloud representing a contour line or the like on the image);
determining at least one tile having a two-dimensional area and a zoom level (para 0160-0167; a pathological image being divided into tile images (i.e., two-dimensional area) and then generating a pyramid structure by repeating and combining tiles. The different layers have different resolutions or magnifications (i.e., zoom levels), allowing the detailed level of the displayed observation target to change);
selecting from the point cloud those points having a location within the two-dimensional area (para 0094; the conversion unit 104 can convert point cloud coordinate data, which is obtained by converting the annotation data 802 serving as the reference into data as point cloud coordinates, into other annotation data 802);
based on the selected points and the zoom level, determining a set of display points, each point of the set of display points representing a feature of the biological sample at its corresponding location (fig. 11; para 0095-0100 and 0167-0168; in conversion into low magnification, conversion to point cloud display (at points, distribution of nuclei is shown) illustrated in the upper center of FIG. 11; The display control device 5513 extracts a desired tile image from the tile image group of the pyramid structure according to the input operation from the user and outputs the desired tile image to the display device 5514. With such processing, the user can obtain a feeling as if the user is observing the observation target while changing observation magnification);
providing the set of display points for display at the zoom level (para 0099, 0113, and 0167; outputting the converted annotation data; Displaying the point cloud representation of the distribution of nuclei; The display control device 5513 extracts a desired tile image from the tile image group of the pyramid structure according to the input operation from the user and outputs the desired tile image to the display device 5514).
Regarding claim 2, the method of claim 1, Teramoto discloses wherein determining the set of display points comprises randomly subsampling the selected points based on the zoom level (para 0095-0100).
Regarding claim 3, the method of claim 2, Teramoto discloses wherein the randomly subsampling the selected points comprises removing approximately half of the selected points (para 0095-0110).
Regarding claim 4, the method of claim 2, Teramoto discloses wherein the randomly subsampling the selected points comprises removing a portion of the selected points proportionate to the zoom level (para 0095-0110).
Regarding claim 5, the method of claim 1, Teramoto discloses wherein determining the set of display points comprises:
clustering the selected points based on the zoom level, yielding a plurality of clusters (fig. 11; para 0095-0100 and 0167-0168); and
defining a display point for each of the plurality of clusters (fig. 11; para 0095-0100 and 0167-0168).
Regarding claim 7, the method of claim 5, Teramoto discloses wherein defining each point comprises determining a summary statistic for the corresponding cluster (para 0099 and 0162-0167).
Regarding claim 8, the method of claim 7, Teramoto discloses wherein the summary statistic comprises a count of the points within the corresponding cluster (para 0094, 0099, and 0162-0167).
Regarding claim 9, the method of claim 8, Teramoto discloses wherein each display point has a visual attribute corresponding to the summary statistic (para 0099, 0108, and 0160-0161).
Regarding claim 10, the method of claim 9, Teramoto discloses wherein the visual attribute is a size or color (para 0099, 0108, and 0160-0161).
Regarding claim 11, the method of claim 1, Teramoto discloses further comprising displaying the set of display points on a display (para 0113 and 0167).
Regarding claim 12, the method of claim 11, Teramoto discloses wherein displaying the set of display points comprises superimposing the set of display points on an image of the biological sample (fig. 11; para 0050 and 0099).
Regarding claim 13, the method of claim 12, Teramoto discloses wherein superimposing comprises registering the set of display points to the image of the biological sample (fig. 11; para 0050 and 0099).
Regarding claim 14, the method of claim 1, Teramoto discloses wherein the set of display points is determined at a server side in response to a request from a remote client, and wherein providing the set of display points for display comprises sending the display points from the server to the remote client (para 0160-0166 and 0172).
Regarding claim 15, the method of claim 1, Teramoto discloses wherein the at least one tile comprises a plurality of tiles together defining a display port on a GUI (para 0162-0167).
Regarding claim 16, the method of claim 1, Teramoto discloses further comprising:
receiving an adjusted zoom level (para 0112-0113 and 0163);
based on the adjusted zoom level, determining at least one additional tile having an adjusted two-dimensional area at the adjusted zoom level (para 0160-0167);
selecting from the point cloud those points having a location within the adjusted two-dimensional area (para 0094);
based on the selected points having a location within the adjusted two-dimensional area and the adjusted zoom level, determining an adjusted set of display points, each point of the adjusted set of display points representing a feature of the biological sample at its corresponding location (fig. 11; para 0095-0100 and 0167-0168);
providing the adjusted set of display points for display at the adjusted zoom level (para 0099, 0113, and 0167).
Regarding claim 17, this claim recites substantially the same limitations that are performed by claim 1 above, and it is rejected for the same reasons.
Regarding claim 33, this claim recites substantially the same limitations that are performed by claim 1 above, and it is rejected for the same reasons.
Regarding claim 46, this claim recites substantially the same limitations that are performed by claim 14 above, and it is rejected for the same reasons.
Regarding claim 48, this claim recites substantially the same limitations that are performed by claim 16 above, and it is rejected for the same reasons.
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.
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Teramoto et al., US 2024/0152692 in view of Mellen et al., US 2021/0097684.
Regarding claim 6, the method of claim 5, Teramoto discloses wherein clustering the selected points (fig. 11; para 0095-0100 and 0167-0168).
Teramoto discloses claim 6 as enumerated above, but Teramoto does not explicitly disclose comprises performing DBSCAN clustering, OPTICS clustering, or K-Means clustering as claimed.
However, Mellen discloses the clustering of all or a subset of the probe spots comprises k-means clustering with K set to a predetermined value between one and twenty-five (para 0021 and 0214).
Therefore, taking the combined disclosures of Teramoto and Mellen as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the clustering of all or a subset of the probe spots comprises k-means clustering with K set to a predetermined value between one and twenty-five as taught by Mellen into the invention of Teramoto for the benefit of clustering the discrete attribute value dataset based upon the principal components or the discrete attribute values of individual probe spots into K partitions (Mellen: para 0214).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Lovli et al., US 2024/0193864 discloses a computer-implemented method for visualizing sensor data in a three-dimensional virtual representation of a terrain that has multiple surface layers.
Yin et al., US 2021/0155982 discloses systems and methods for spatial analysis of analytes include placing a sample on a substrate having fiducial markers and capture spots.
Zhao et al., US 2023/0034263 discloses for in situ spatial profiling of biological materials such as DNA, RNA and protein in cells, tissues, and organisms for investigating biology and for conducting biomarker/drug discovery and development, and for clinical pathology and diagnosis.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to VAN D HUYNH whose telephone number is (571)270-1937. The examiner can normally be reached 8AM-6PM.
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/VAN D HUYNH/Primary Examiner, Art Unit 2665
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