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 .
Specification
The disclosure is objected to because of the following informalities:
In Paragraph 1, line 6, “the presently disclosed subject matter” should read as “The presently disclosed subject matter.”
Appropriate correction is required.
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.
Claim 16 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim does not fall within at least one of the four categories of patent eligible subject matter because the claim as presently drafted encompasses both transitory and non-transitory embodiments. Specifically, the claim recites “a transitory or non-transitory computer readable medium (1000)” which is broad enough to include transitory forms such as carrier waves or signals. A transitory signal, while physical and real, does not possess concrete structure that would qualify as a device or part under the definition of a machine, is not a tangible article or commodity under the definition of a manufacture (even though it is man-made and physical in that it exists in the real world and has tangible causes and effects), and is not composed of matter such that it would qualify as a composition of matter. As such, a transitory, propagating signal does not fall within any statutory category.
Claim Rejections - 35 USC § 102
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.
Claims 1, 2, 4, 6-9, 12, and 14-16 are rejected under 35 U.S.C. 102 (a)(1) as being anticipated by Kallioniemi et al. (US2004085443A1).
Regarding Claim 1, Kallioniemi teaches a method (700) for planning treatment of an area of interest on a tissue section with a motorized treatment tip, the motorized treatment tip being arranged for treating multiple treatment areas having a geometric shape, the method comprising:
Paragraph [0095]: “Then, at 416, an operation can be performed on a physical location within the region of interest. For example, material can be extracted from the region of interest. To perform the operation, information specifying a physical location within the region of interest can be determined. For example, for a particular location chosen with respect to a perimeter of the region of interest, an appropriate translation mechanism can be determined and applied to generate information for sending to a controller to position an automated positioning device appropriate for performing the operation at the physical location corresponding to the chosen location. The information specifying a physical location can be determined at least in part based on the information specifying the location and extent of the region of interest.”
obtaining (710) one or more images representing a tissue section, an area of interest which is part of the tissue section, and background,
Paragraph [0104]: “At 704, an image representative of the physical object is captured.”
Paragraph [0106]: “The system 802 includes an image capturing device 822 that captures an image of the physical object 808 and sends it to a computer system 832.”
Explanation: This includes tissue section, area of interest, and background.
iteratively (720) perform - computing (721) for each pixel in the area of interest a distance to the nearest pixel in the tissue section outside the area of interest or in the background,
Paragraph [0115]: “The location of a perimeter point (e.g., P₁) with respect to the reference points can be described as a set of distances (e.g., D₁, D2, and D3) from the reference points. Therefore, to describe the location and extent of the region of interest 1004 according to the example, the computer system performs the following for the perimeter points in the region of interest 1004: the software calculates the distances between the point and the reference points and stores the distances in a computer-readable medium so the information can be retrieved later and be used to reconstruct the location and extent of the region of interest 1004.”
Explanation: Distance-based Region of Interest (ROI) processing is the same concept.
applying (722) a distance transform to the distance, the distance transform having a preferred value for a radius of the geometric shape and having less preferred values for values higher and/or lower than the radius,
Paragraph [0155]: “Perimeter points can be defined as the intersection of three circles, each circle defined as centered about a reference point and having a radius equal to the defined distance.”
Explanation: This is explicitly a radius-based distance transform style evaluation.
selecting (723) a position for a treatment area from the result of the distance transform,
Paragraph [0130]: “At 1322, a location within the region of interest is chosen.”
recording (724) the selected position for a treatment area, and removing from the area of interest a geometric shape corresponding to a treatment area at the selected position.
Paragraph [0020]: “For example, the database can be updated to reflect the amount and location of remaining material.”
Paragraph [0190]: “Then, at 1944, material is extracted from the physical object at the chosen location within the region of interest.”
Regarding Claim 2, Kallioniemi teaches a method as in Claim 1, wherein removing from the area of interest a geometric shape corresponding to a treatment area at the selected position comprises amending the images to marking said geometric shape as non-area of interest, e.g., as tissue section or as background.
Paragraph [0020]: “Information for the block can be updated to indicate removed tissue is no longer available in the block.”
Regarding Claim 4, Kallioniemi teaches a method as in Claim 1, comprising computing an expected treatment gain for the pixels, wherein selecting a position for a treatment area depends on the expected treatment gain.
Paragraph [0020]: “For example, characteristics can be denoted for regions of interest, so software can select appropriate regions of interest based on supplied criteria for a recipient block.”
Paragraph [0187]: “The location within the region of interest can be chosen with operator assistance or automatically by software, based on various specified criteria (e.g., near the center, near an edge, or according to another scheme).”
Explanation: This shows candidate location scoring and selection criteria, which corresponds to gain/optimization selection.
Regarding Claim 6, Kallioniemi teaches a method as in Claim 1, wherein the motorized treatment tip, is arranged for treating areas having multiple different geometric shapes, the iteration being performed for at least two different geometric shapes.
Paragraph [0102]: “The regions of interest can take a variety of shapes and sizes.”
Regarding Claim 7, Kallioniemi teaches a method as in Claim 6, wherein the iterations are performed for geometric shapes from largest radius to smallest radius.
Paragraph [0022]: “The scaling information mentioned above can be helpful in the tissue block context because the scaling information can be used to assist in selection and implementation of tissue punch size and punch spacing.”
Explanation: This shows punch size hierarchy and spacing optimization, which corresponds to radius ordering.
Regarding Claim 8, Kallioniemi teaches a method as in Claim 1, wherein the geometric shapes are circles.
Paragraph [0155]: “Perimeter points can be defined as the intersection of three circles, each circle defined as centered about a reference point and having a radius equal to the defined distance.”
Regarding Claim 9, Kallioniemi a method as in Claim 1, comprising computing a maximal distance for the pixels in the area of interest a distance to the nearest pixel in the tissue section outside the area of interest or background, and deciding from the maximal distance to perform the remainder of the iteration or to abort the remainder of the iteration.
Paragraph [0164]: “The software can accept parameters to assist in selection of plural locations for a region of interest. For example, an operator might specify that a particular set of locations be chosen based on an amount of material to be extracted for each location, and a minimum distance between each location.”
Explanation: This shows the selection of extraction feasibility and distance constraints, as well as feasibility/remaining resource decisions.
Regarding Claim 12, Kallioniemi a method as in Claim 1, wherein treating in a treatment area comprises detaching of tissue in a detachment area.
Paragraph [0005]: “The process of constructing the recipient block can include retrieving the donor blocks, removing (i.e., punching) tissue from the donor blocks, and placing the tissue into a recipient block.”
Regarding Claim 14, Kallioniemi teaches all the limitations as in the consideration of claim 1 above. Kallioniemi further teaches the one or more processors and one or more storage devices that perform the same steps as claim 1 (Fig. 40 (shown below)).
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Regarding Claim 15, Kallioniemi a method as in Claim 14, comprising the motorized treatment tip, the operations including:
imaging the first tissue slice and obtaining the one or more images therefrom,
Paragraph [0012]: “In some cases, a slice is easier to observe and manipulate, so the region of interest can be indicated for the slice.”
Paragraph [0104]: “At 704, an image representative of the physical object is captured.”
Paragraph [0146]: “The digital image data from the camera 1506 comprises a representation of the object 1512.”
performing treatment on the second tissue slice as planned with the motorized treatment tip.
Paragraph [0005]: “The process of constructing the recipient block can include retrieving the donor blocks, removing (i.e., punching) tissue from the donor blocks, and placing the tissue into a recipient block.”
Paragraph [0095]: “Then, at 416, an operation can be performed on a physical location within the region of interest.
Paragraph [0140]: “In the example, the platform 1520 is an automated positioning device and is moveable via motors 1522, which are controlled by controllers 1521.”
Paragraph [0196]: “In one example, the automated device 1562 is an automated extractor (e.g., a tissue punch) for extracting material. Commands can be sent to the controller 1552 so that the extractor 1562 extracts material from the physical object 1512.”
Regarding Claim 16, Kallioniemi teaches all the limitations as in the consideration of claim 1 above. Kallioniemi further teaches the computer readable medium that perform the same steps as claim 1.
Paragraph [0107]: “The computer system 832 can be any of a variety of systems, including commercially-available systems that support any of a variety of computer-readable media (e.g., RAM, a hard disk, a computer-readable CD, and the like) for storing information. “
Paragraph [0145]: “Storage 1540 can be implemented via any of a variety of computer-readable media.”
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 3, 10, and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Kallioniemi in view of Felzenszwalb and Huttenlocher (“Distance Transforms of Sampled Functions”).
Regarding Claim 3, Kallioniemi teaches a method as in Claim 1, but fails to teach that the distance transform comprises a quadratic term (R - d)2, or absolute linear term abs (R - d), e.g., 1 - (R - d)2/R2, wherein R represents the radius and d represent the distance.
However, Felzenszwalb and Huttenlocher explicitly teach quadratic distance transforms, stating that “the squared Euclidean (or quadratic) distance transform of f is given by Df (p) = min ((p-q)2 + f(q))” (Equation 2.1). The reference further explains that “the distance transform is defined by the lower envelope of these parabolas, as shown in Figure 1” (2.1 One dimension, pg. 419), and that they consider “a generalization of distance transforms to arbitrary functions on a grid rather than binary-valued ones (i. e., real-valued images rather than binary images) …which in this case should reflect a combination of distances and feature costs” (Introduction, pg. 415 and 416). These excerpts explicitly teach quadratic distance formulation, distance-based scoring, pixel selection based on distance transform, and optimization framework for spatial selection.
Thus, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Kallioniemi’s distance-based region selection to use the quadratic distance transforms. Felzenszwalb and Huttenlocher explain why quadratic distance transforms are used, stating that “distance transforms are an important tool in computer vision, image processing and pattern recognition” (Introduction, pg. 415), and “distance transforms of sampled functions arise in the solution of a number of optimization problems” (1.2 Optimization problems, pg. 418). Since quadratic distance transforms improve spatial optimization and selection tasks, using them would have predictably improved the accuracy and mathematical rigor of selecting treatment locations within a region of interest.
Regarding Claim 10, Kallioniemi teaches a method as in Claim 1, but fails to teach that it comprises computing for each pixel a constraints score indicating a suitability for receiving a treatment area, a final score being computed as a product of the constraints score and the transformed distance. While Kallioniemi teaches computing suitability information for pixels/locations, he does not explicitly disclose computing a final score using a mathematical combination with a distance transform.
However, Felzenszwalb and Huttenlocher explicitly teach combining distance with a cost function per pixel, stating that “rather than using a binary array to specify the presence or absence of a feature at each pixel, it can be useful to have a real-valued array specifying a cost (or strength) for a feature at each pixel” (Introduction, pg. 415). The reference defines the distance transform as “Df (p) = min (d(p,q)+ f(q))” (Equation 1.1), which explicitly combines distance with a cost/constraint value. The reference also explains that the transform reflects “a combination of distances and feature costs” (Introduction, pg. 416).
Thus, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Kallioniemi to compute a final score combining a per-pixel suitability/constraint score and a distance transform-derived value. Felzenszwalb and Huttenlocher state that distance transforms incorporate spatial distance together with feature cost to evaluate candidate pixel locations. Thus, a person of ordinary skill in the art would have been motivated to apply the known distance-transform scoring technique of Felzenszwalb and Huttenlocher to the suitability evaluation of Kallioniemi in order to improve selection of candidate treatment locations, incorporate spatial spacing/geometry, and compute optimal placement using combined constraints and distance.
Regarding Claim 11, Kallioniemi in view of Felzenszwalb and Huttenlocher teaches a method as in Claim 10, and Kallioniemi further teaches that the constraints score, penalizes a treatment area outside the area of interest and/or a treatment area outside a tissue slide section of the image.
Paragraph [0019/0020/0021]: “The information indicating the region of interest is then stored… For example, characteristics can be denoted for regions of interest, so software can select appropriate regions of interest based on supplied criteria for a recipient block… Other information about a tissue block can be stored to assist in selecting an appropriate region of interest.
Paragraph [0116]: “The technique can also be used to describe regions inside a region of interest that are designated as not part of the region of interest (e.g., the excluded region 1062).”
Claim 5 is under 35 U.S.C. 103 as being unpatentable over Kallioniemi in view of Nemhauser and Wolsey (“An Analysis of Approximations for Maximizing Submodular Set Functions”).
Regarding Claim 5, Kallioniemi teaches a method as in Claim 4, but fails to teach that the iteration is continued until the incremental gains are below a threshold.
However, Nemhauser and Wolsey teach stopping-criterion, stating that “Step 1. If Pt-1< 0, stop with the set Sk*, K*=t-I<K. If pt-l > 0, set St = S t-1 U {i(t)} and Nt = N t-1-{i(t)}. Continue.” (4. The greedy heuristic for submodular set functions, pg. 277). This explicitly teaches computing incremental gain p, comparing that gain to a threshold (0), continuing iteration only while gain exceeds the threshold, and stopping when gain falls below the threshold.
Thus, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to apply this optimization stopping criterion to the iterative treatment-planning process of Kallioniemi. Nemhauser and Wolsey state that “If S, |S| =p, is the approximate
solution for K = p, then the approximate solution for K = p + 1 is determined by adding to S (if possible) a j* such that z(S U{]*})= maxj~sz(S U{j}) and z(S U {j*}) > z(S)… the procedure stops when no such improvement is possible” (pg. 268). They also state that “if the greedy heuristic is applied to problem (1.6) with z nondecreasing and stops after K* < K steps, the greedy solution is optimal” (Section 4, Proposition 4.2, pg. 278), and “the number of iterations required by the interchange heuristic depends on the method used to find improving solutions…a poor method can take an exponential number of iterations…” (pg. 287). Nemhauser and Wolsey show that iterative placement processes evaluate improvement per iteration and terminate when the incremental improvement becomes sufficiently small, thereby avoiding unnecessary computation and inefficiency. Therefore, a person of ordinary skill in the art would have been motivated to incorporate stopping criterion based on diminishing incremental gain to improve efficiency of automated tissue processing, avoid selecting locations that provide negligible benefit, and optimize placement decisions.
Claim 13 is under 35 U.S.C. 103 as being unpatentable over Kallioniemi in view of Ott et. al (US 20240418611 A1).
Regarding Claim 13, Kallioniemi teaches a method as in Claim 12, but fails to teach that it comprises applying lysing chambers having the geometric shapes corresponding to detachment areas, dispensing a detaching liquid to the lysing chamber, allowing the detaching liquid to detach tissue, aspirating the detaching liquid with the detached tissue from the cavity, and forwarding the liquid for further processing.
However, Ott discloses that a “3D printed mask comprises barriers that define a cavity surrounding an area of interest on the tissue section…the cavity is also referred to as a detachment chamber…If lysing is used, this may be referred to as a lysing chamber” (paragraph [0072]). Then, “a detaching liquid may be dispensed into the cavity, and later aspirated from the cavity together with detached tissue…a desired further processing may then be applied to the detached tissue, e.g., genomic analysis, storing the tissue, or the like” (paragraph [0009]).
Thus, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Kallioniemi to incorporate this method for detaching tissue from a tissue section. Ott discloses numerous benefits of this approach, including improved throughput (paragraphs [0015] and [0105]), parallel detaching (paragraphs [0015] and [0041]), precise matching of area geometry (paragraphs [0011] and [0129]), and collection of detached tissue for downstream processing (paragraphs [0008], [0009], and [0076]). Therefore, a person of ordinary skill in the art would have been motivated incorporate this chamber-based detachment approach into Kallioniemi to improve precision, enable parallel detaching, and facilitate collection for analysis.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Ren et. al (“Treatment Planning and Image Guidance for Radiofrequency Ablation of Large Tumors”) teaches a systematic approach to needle-based ablation placement, ranging from preoperative planning algorithms to an intraoperative execution platform. The planning system incorporates clinical constraints on ablations and trajectories using a multiple objective optimization formulation, which consists of optimal path selection and ablation coverage optimization based on integer programming.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WILLIAM ADU-JAMFI whose telephone number is (571) 272-9298. The examiner can normally be reached M-T 8:00-6:00.
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/WILLIAM ADU-JAMFI/Examiner, Art Unit 2677
/ANDREW W BEE/Supervisory Patent Examiner, Art Unit 2677