PATENT CLAIM ANALYSIS

Application Number: 15764789
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2018-11
Patent Classification: ["382", "131000"]

Abstract:
A medical data processing method, performed by a computer ( 2 ), for determining error analysis data describing the registration accuracy of a first elastic registration between first and second image data (A, B) describing images of an anatomical structure of a patient, comprising the steps of: —acquiring the first image data (A) describing a first image of the anatomical structure, —acquiring the second image data (B) describing a second image of the anatomical structure, —determining first registration data describing a first elastic registration of the first image data (A) to the second image data (B) by mapping the first image data (A) to the second image data (B) using a registration algorithm, —determining second registration data describing a second elastic registration of the second image data (B) to the first image data (A) by mapping the second image data (B) to the first image data (A) using the registration algorithm, —determining error analysis data describing the registration accuracy of the first elastic registration based on the first registration data and the second registration data.

Claim (Index 25):
A computer, comprising a non-transitory computer-readable program storage medium storing a computer program which, when executed by at least one processor of the computer, causes the computer to perform a medical data processing method for determining error analysis data describing the registration accuracy of a first elastic registration between first and second image data describing images of an anatomical structure of a patient, the method comprising the steps of:\n acquiring, at the at least one processor, the first image data describing a first image of the anatomical structure; acquiring, at the at least one processor, the second image data describing a second image of the anatomical structure; determining, by the at least one processor, first registration data describing a first elastic registration of the first image data to the second image data by mapping the first image data to the second image data using a registration algorithm; determining, by the at least one processor, second registration data describing a second elastic registration of the second image data to the first image data by mapping the second image data to the first image data using the registration algorithm; determining, by the at least one processor, error analysis data describing the registration accuracy of the first elastic registration based on the first registration data and the second registration data; wherein determining error analysis data comprises determining observed errors for a plurality of data points within the first image data; wherein determining error analysis data comprises determining at least one statistical parameter from the plurality of observed errors; wherein determining error analysis data comprises defining at least one data area within the first image data and determining at least one local statistical parameter for the observed errors obtained for data points within the at least one data area; wherein the method further includes the step of acquiring, at the at least one processor, critical structure data describing the position of at least one critical structure corresponding to a region of interest within the anatomical structure in the first image data and calculating the distance between the position of the critical structure and the position of at least one data area within the first image data.

Metadata:
- Claim Count in Document: 32.0
- Percentile: 90.0
- Lexical Diversity: 4.5
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15611492', '15533307', '15547723', '11985526', '14437789']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3055294095536785
- 35 USC 102 Novelty (BERT): 0.4628033818936488
- Combined Prediction Score: 0.3212568067876755
- Mean Citation Score: 166.841058
- Max Citation Score: 171.33795
- Similarity Product: 138.45257795024514

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test