PATENT CLAIM ANALYSIS

Application Number: 16412290
Application Type: Utility
Filing Date: 2019-05
Publication Date: 2019-10
Patent Classification: ["382", "131000"]

Abstract:
An improved system and method for estimating and compensating for motion by reducing motion artifacts produced during image reconstruction from helical computed tomography (CT) scan data. In a particular embodiment, the reconstruction may be based on helical partial angle reconstruction (PAR) and the registration may be performed utilizing one or more artificial intelligence (AI) based methods.

Claim (Index 9):
The method of  claim 1 , wherein performing image registration of the first partial image and the second partial image for each pair of the subset to estimate a deformation that transforms the first partial image into the second partial image further comprises:\n convolving the first partial image and the second partial image using a first plurality of filters to generate a first plurality of convolved images; performing a nonlinear activation function on the first plurality of convolved images to generate a first plurality of intermediate images; convolving the first plurality of intermediate images using a second plurality of filters to generate a second plurality of convolved images; performing a nonlinear activation function on the second plurality of convolved images to generate the second plurality of intermediate images; and repeating the steps of convolving the intermediate images using a plurality of filters and performing a nonlinear activation function on the convolved images for a predetermined number of iterations to generate a deformation map that estimates the deformation that transforms the first partial image into the second partial image.

Metadata:
- Claim Count in Document: 23.0
- Percentile: 100.0
- Lexical Diversity: 1.32653
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15815662', '14554799', '14838522', '12930856', '12032810']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3801792972090176
- 35 USC 102 Novelty (BERT): 0.535395282815217
- Combined Prediction Score: 0.3957008957696376
- Mean Citation Score: 239.789886
- Max Citation Score: 371.74078
- Similarity Product: 284.5282852509665

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

Dataset: test