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 5):
The method of  claim 1 , wherein the artificial intelligence based method for performing the image registration is selected from a Deep Learning based method and a Convolutional Neural Network (CNN) based method.

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): 0.3820068223100118
- 35 USC 102 Novelty (BERT): 0.5354214513321457
- Combined Prediction Score: 0.3973482852122252
- Mean Citation Score: 239.789886
- Max Citation Score: 371.74078
- Similarity Product: 210.918420820781

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