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 § 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 28 is directed to data structures embodied on a computer readable medium. The broadest reasonable interpretation of a claim drawn to a computer readable medium includes forms of non-transitory tangible media and transitory propagating signals per se in view of the ordinary and customary meaning of computer-readable media. See Subject Matter Eligibility of Computer Readable Medium, Jan. 26, 2010. The Applicant’s specification does not limit computer readable medium to non-transitory embodiments, and therefore claim 28 is non-statutory. The Examiner suggests amending the claim to include “non-transitory computer readable medium” or similar language.
Claims 1-28 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more.
Regarding claims 1-28, under the broadest reasonable interpretation, the terms of the claims are presumed to have their plain meaning consistent with the specification as it would be interpreted by one of ordinary skilled in the art. See MPEP 2111.
The claimed invention related to a method includes applying a transfer function to a 3D grid of voxels generated from the scan data, each voxel having an associated intensity value, to determine a density value associated with each voxel. The method further includes generating a 3D grid of super voxels, each super voxel being formed from a plurality of adjacent voxels of the 3D grid of voxels, each super voxel having an associated density value. The method further includes performing an optimization using the 3D grid of super voxels, based at least in part on a defined super voxel size. The method further includes drawing a 3D volume based at least in part on the 3D grid of super voxels and the determined density associated with each super voxel.
The claims are directed mental processing and does/do not fall within at least one of the four categories of patent eligible subject matter because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea).
The claims do not have any limitations that are indicative of integration of the judicial exception into a practical application such as improvements to functioning of a computer or a technical field, using any particular machine, effect a transformation of a particular article to a different state or thing, or apply the judicial exception in any meaningful way beyond generally linking the use to a particular technological environment. Therefore, the claims as a whole do not amount to significantly more than the judicial exception.
A patent may be obtained for “any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof," 35 U.S.C. § 101, but “laws of nature, natural phenomena, and abstract ideas are not patentable.”
Step 1: Claims 1-28 are directed to one of the four statutory categories of eligible subject matter: thus, the claims pass Step 1 of the Subject Matter Eligibility Test.
Step 2A, prong 1 analysis
Claims 1-28 recite a judicial exception in terms of a mental process. Steps in claims 1-28 can be performed by a human being thinking in mind to use a computer to “applying a transfer function to a 3D grid of voxels generated from the scan data, each voxel having an associated intensity value, to determine a density value associated with each voxel; generating a 3D grid of super voxels, each super voxel being formed from a plurality of adjacent voxels of the 3D grid of voxels, each super voxel having an associated density value; performing an optimization using the 3D grid of super voxels, based at least in part on a defined super voxel size; and drawing a 3D volume based at least in part on the 3D grid of super voxels and the determined density associated with each super voxel.”.
Step 2A, prong 2 analysis
The judicial exception is not integrated into a practical application for improving technological field as there is no additional element claimed other than the judicial exception.
This judicial exception is not integrated into a practical application because additional elements of:
“a graphics processing unit (GPU) and a central processing unit, computer storage...” are generically recited computer elements that do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer.
Step 2B
Further, the claims do not include other additional elements that are beyond what is well- understood, routine, conventional activities in the field and sufficient to amount to significantly more than the judicial exception.
Conclusion:
The claims do not include additional elements amount to significantly more in terms of improving functionalities of a computer/device itself, improving another technology or technical field, effecting a transformation or reduction of a particular article to a different state or thing, adding unconventional steps that confine claim to a particular useful application or by use of a particular machine that is unconventional. In conclusion, the claims 1-28 do not comply with the current standards for patent eligible subject matter under 35 USC § 101.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Ozdemir et al. (USPGPUB 2019/012073) teaches a system and method for quantifying uncertainty in reasoning about 2D and 3D spatial features with a computer machine learning architecture.
Rybnikov et al (USPGPUB 2023/0386153) teaches a computer-implemented method includes obtaining a three-dimensional (3D) image of a region of a body of a patient, the 3D image having feature values.
Li (CN 110556176) teaches a dose-based optimization method, device and storing medium of Monte Carlo.
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/BENNY Q TIEU/ Supervisory Patent Examiner, Art Unit 2682