DETAILED ACTION
[1] Remarks
I. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
II. Claims 13-24 are pending and have been examined, where claims 13-16, 19 and 23-24 is/are rejected and claim 17-18 and 20-21 is/are objected to. Explanations will be provided below.
III. Inventor and/or assignee search were performed and determined no double patenting rejection(s) is/are necessary.
IV. Patent eligibility (updated in 2019) shown by the following: Claims 13-24 pass patent eligibility test because there is/are no limitation or a combination of limitations amounting to an abstract idea. Also, the following limitation or the combinations of the limitations: “pruning the venous vessels segmentation to retain only major vessels and determining a primary hepatic zone from the retained major vessels, wherein determining the primary hepatic zone comprises determining a convex hull of the retained major vessels; - determining at least one quantitative feature from at least one of the primary hepatic zone, the liver segmentation and the one or more liver lesion segmentation” effects a transformation or a reduction of a particular article to a different state or thing / adds a specific limitation(s) other than what is well-understood, routine and conventional in the field, or adding unconventional steps that confine the claim to a particular useful application and providing improvements to the technical field of image segmentation, which recite additional elements that integrate the judicial exception into a practical application and amounting significant more.
[2] Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
Use of the word “means” (or “step for”) in a claim with functional language creates a rebuttable presumption that the claim element is to be treated in accordance with 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph). The presumption that 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph) is invoked is rebutted when the function is recited with sufficient structure, material, or acts within the claim itself to entirely perform the recited function. Absence of the word “means” (or “step for”) in a claim creates a rebuttable presumption that the claim element is not to be treated in accordance with 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph). The presumption that 35 U.S.C. 112(f) (pre-AIA 35 U.S.C. 112, sixth paragraph) is not invoked is rebutted when the claim element recites function but fails to recite sufficiently definite structure, material or acts to perform that function.
Claim elements in this application that use the word “means” (or “step for”) are presumed to invoke 35 U.S.C. 112(f) except as otherwise indicated in an Office action. Similarly, claim elements that do not use the word “means” (or “step for”) are presumed not to invoke 35 U.S.C. 112(f) except as otherwise indicated in an Office action.
Claim(s) 23 are not interpreted under 35 U.S.C. 112(f) or pre-AIA U.S.C. 112 6th paragraph because of the following reason(s): limitations are modified by sufficient structure or material for performing the claimed function.
Claim(s) 13-22 and 24 do not require 35 U.S.C. 112(f) or pre-AIA U.S.C. 112 6th paragraph interpretation because they are method claims and / or they are CRM claims.
Upon examination of the specification and claims, the examiner has determined, under the best understanding of the scope of the claim(s), rejection(s) under 35 U.S.C. 112(a)/(b) is not necessitated because of the following reasons: sufficient support are provided in the written description / drawings of the invention.
[3] Grounds of Rejection
Claim Rejections - 35 USC § 103
1. 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.
2. Claims 13, 15-16, 19 and 22-24 is/are rejected under 35 U.S.C. 103 as being unpatentable over SIMPSON (US 20190019300) in view of Selle et al. (D. Selle, B. Preim, A. Schenk and H. . -O. Peitgen, "Analysis of vasculature for liver surgical planning," in IEEE Transactions on Medical Imaging, vol. 21, no. 11, pp. 1344-1357, Nov. 2002).
Regarding claim 13, SIMPSON discloses a computer-implemented method of liver resection planning, comprising the steps of:
processing preoperative tomographic images of a patient to generate a liver segmentation, one or more liver lesion segmentation and venous vessels segmentations (see figure 1, step 1, segmentation and model generation, the liver region is segmented along with the vessels and venous regions);
PNG
media_image1.png
248
609
media_image1.png
Greyscale
pruning the venous vessels segmentation to retain erosion operators slightly expanded the tumor and vessel boundaries to compensate for potential small inaccuracies in the segmentation, where the erosion is read as pruning);
PNG
media_image2.png
241
667
media_image2.png
Greyscale
determining at least one quantitative feature from at least one of the primary hepatic zone, the liver segmentation and the one or more liver lesion segmentation (see figure 1, 115 is image histogram, which is read as image features);
predicting a liver resection complexity by processing the determined at least one quantitative feature with a classification model (see paragraph 96, a multiple linear regression was used to model the relationship between combinations of texture features to illustrate the predictive power of texture feature sets, e.g., quantitative imaging phenotypes, tumor for high and low values of five texture variables are shown in the images on FIG. 5A. FIG. 5B shows a schematic diagram of the exemplary prediction model relating protein express to texture features according to an exemplary embodiment of the present disclosure, a CT image 505 can be used in a tumor extraction procedure 510, after the tumor has been extracted, a texture extraction procedure 515 can be performed, the results of which can be input onto a prediction model 525, a protein expression 520 can also be input into prediction model 525, the liver resection complexity is read by the liver region which comprises of plurality of sections, also see paragraph 126, extent of liver resection was classified as major (e.g., 3 or more hepatic segments) or minor, as well as bilateral (e.g., resections involving both hemi-livers) or unilateral).
SIMPSON is silent in disclosing pruning the venous vessels segmentation to retain only major vessels and determining a primary hepatic zone from the retained major vessels, wherein determining the primary hepatic zone comprises determining a convex hull of the retained major vessels.
Selle discloses pruning the venous vessels segmentation to retain only major vessels and determining a primary hepatic zone from the retained major vessels, wherein determining the primary hepatic zone comprises determining a convex hull of the retained major vessels (see figure 3, only major vessels are extracted, b graphs G of two touching vessel systems, see illustration below).
PNG
media_image3.png
421
791
media_image3.png
Greyscale
.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include pruning the venous vessels segmentation to retain only major vessels and determining a primary hepatic zone from the retained major vessels in order to reduce topological noise and errors, where the peripheral, tiny blood vessels are highly prone to segmentation errors, false positives, and artifacts.
Regarding claim 15, SIMPSON discloses the computer-implemented method of claim 13, wherein the classification model is a classifier (see paragraph 168, fMRMR was chosen due to its simplicity and comparable performance with the other procedures, e.g., stepwise logistic regression, fisher score, and wrapper, logistic regression is a classifier).
Regarding claim 16, SIMPSON discloses the computer-implemented method of claim 15, wherein the classifier is a binary classifier trained to predict either a complex or not complex liver resection based on at least one quantitative feature (see paragraph 126, The extent of liver resection was classified as major, or minor, major and minor are read as complex and not complex respectively).
Regarding claim 19, SIMPSON discloses the computer-implemented method of claim 13, wherein the at least one quantitative feature includes a relative position of each of the one or more liver lesion segmentation with respect to the primary hepatic zone (see figure 1, 115, the histogram shown includes the entire liver region which includes the hepatic zone).
Regarding claim 22, SIMPSON discloses the computer-implemented method of claim 19, wherein the at least one quantitative feature further comprises a liver volume, a number of lesions and a volume of lesions (see figure 1, 120).
Regarding claims 23 and 24, SIMPSON discloses a data processing apparatus comprising a processor configured to perform the steps of the method of claim 13 (see figure 30 3004).
3. Claim 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over SIMPSON (US 20190019300) in view of Selle et al. (D. Selle, B. Preim, A. Schenk and H. . -O. Peitgen, "Analysis of vasculature for liver surgical planning," in IEEE Transactions on Medical Imaging, vol. 21, no. 11, pp. 1344-1357, Nov. 2002) and Dhatt (US 20190339371).
Regarding claim 14, the combination of SIMPSON and Selle as a whole discloses all the limitations of claim 13, but is silent in disclosing the computer-implemented method of claim 13, wherein processing the preoperative tomographic images to generate the liver segmentation, the one or more liver lesion segmentation and the venous vessels segmentations comprises processing the preoperative tomographic images by a first pre-trained neural network to segment the liver and the one or more liver lesion and by a second pre-trained neural network to segment the venous vessels. Dhatt discloses the computer-implemented method of claim 13, wherein processing the preoperative tomographic images to generate the liver segmentation, the one or more liver lesion segmentation and the venous vessels segmentations comprises processing the preoperative tomographic images by a first pre-trained neural network to segment the liver (see paragraph 24, if liver tissue is identified in an ultrasound image, a section of the image containing the liver tissue is segmented and a style selected to enhance the appearance of liver tissue is applied to the segmented portion) and the one or more liver lesion and by a second pre-trained neural network to segment the venous vessels (see paragraph 24, If a blood vessel, e.g. artery, vein, is identified in the image then that portion of the image may be segmented and the same or a different style may be applied to that segment of the image to enhance the appearance of blood in the vessel etc, also see figure 4 illustration below):
PNG
media_image4.png
352
674
media_image4.png
Greyscale
.
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to include processing the preoperative tomographic images by a first pre-trained neural network to segment the liver to reduce background noise by masking out everything outside the liver and analyzing irrelevant tissues. Also, this improves Lesion and vessel accuracy, where venous vessels and tumors have low contrast narrowing the search field to the pre-segmented liver mask.
[4] Claim Objections
Claim(s) 17-18 and 20-21 is/are objected to as being dependent upon a rejected base claim but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
With regards to claim 17, the examiner cannot find any applicable prior art providing teachings for the following limitation(s): the computer-implemented method of claim 13, wherein pruning the venous vessels segmentation comprises: identifying vascular branches and vascular branching networks within the venous vessels segmentation, wherein each vascular branch and vascular branching network has a branch vascular entry; identifying bifurcations within a vascular branching network; pruning said vascular branching network when a pre-set number of vascular bifurcations is reached starting from the branch vascular entry; in combination with the rest of the limitations of claim 13.
Selle discloses the computer-implemented method of claim 13, wherein pruning the venous vessels segmentation comprises:
identifying vascular branches and vascular branching networks within the venous vessels segmentation (see figure 3b, where the segmented vessels are represented using graphs), wherein each vascular branch and vascular branching network has a branch vascular entry (see figure 3b the entry is at the top node);
PNG
media_image5.png
150
733
media_image5.png
Greyscale
identifying bifurcations within a vascular branching network (see figure 3b illustration below);
PNG
media_image6.png
251
403
media_image6.png
Greyscale
Selle does not disclose pruning said vascular branching network when a pre-set number of vascular bifurcations is reached starting from the branch vascular entry (see figure 8, figure 11 and figure 17, do not include pre-set number of vascular bifurcations, the number of vascular, the number of vascular bifurcations depends on the patient’s own vascular structure):
PNG
media_image7.png
258
885
media_image7.png
Greyscale
.
Claim(s) 18 is/are objected as well because it is dependent on a claim with allowable subject matter.
Regarding claim 20, the examiner cannot find any applicable prior art providing teachings for the following limitation(s): the computer-implemented method of claim 19, wherein, when at least one liver lesion segmentation of the one or more liver lesion segmentation do intersect the primary hepatic zone, the relative position of said at least one liver lesion segmentation with respect to the primary hepatic zone consists in a relative occupancy volume of said at least one liver lesion segmentation inside the primary hepatic zone; in combination with the rest of the limitations of claim 13 and 19.
SIMPSON discloses the computer-implemented method of claim 19, wherein, when at least one liver lesion segmentation of the one or more liver lesion segmentation do intersect the primary hepatic zone (paragraph 131, The CT image volume was clipped using the 3D models of the FLR, and hepatic and portal veins to create an image volume containing only the parenchyma of the FLR. A second image volume was created containing only the index tumor. FLR volume was defined as the percentage of remaining functional liver volume compared to the total preoperative functional liver volume, where the parenchyma is within the hepatic zone), but does not disclose the relative position of said at least one liver lesion segmentation with respect to the primary hepatic zone consists in a relative occupancy volume of said at least one liver lesion segmentation inside the primary hepatic zone.
Regarding claim 21, the examiner cannot find any applicable prior art providing teachings for the following limitation(s): the computer-implemented method of claim 19, wherein, when at least one liver lesion segmentation of the one or more liver lesion segmentation do not intersect the primary hepatic zone, the relative position of said at least on liver lesion segmentation with respect to the primary hepatic zone consists in an opposite of a minimal distance from the liver lesion segmentation to the primary hepatic zone; in combination with the rest of the limitations of claim 13 and 19.
SIMPSON, in another embodiment, discloses the computer-implemented method of claim 19, wherein, when at least one liver lesion segmentation of the one or more liver lesion segmentation
HAN (US 20240399172) discloses a distance between the lesion and the target organ is less than a second distance threshold. The target organ has a high impact on body function (e.g., heart, etc.). The first distance threshold and/or the second distance threshold may be preset. The target lesion refers to a lesion that requires a radiotherapy (see paragraph 89), but is silent in disclosing the relative position of said at least on liver lesion segmentation with respect to the primary hepatic zone consists in an opposite of a minimal distance from the liver lesion segmentation to the primary hepatic zone.
CONTACT INFORMATION
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALEX LIEW (duty station is located in New York City) whose telephone number is (571)272-8623 (FAX 571-273-8623), cell (917)763-1192 or email alexa.liew@uspto.gov. Please note the examiner cannot reply through email unless an internet communication authorization is provided by the applicant. The examiner can be reached anytime.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, MISTRY ONEAL R, can be reached on (313)446-4912. 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.
/ALEX KOK S LIEW/Primary Examiner, Art Unit 2674 Telephone: 571-272-8623
Date: 8/26/26
Prosecution Insights