PATENT CLAIM ANALYSIS

Application Number: 16181685
Application Type: Utility
Filing Date: 2018-11
Publication Date: 2019-05
Patent Classification: ["382", "128000"]

Abstract:
Provided are a method and apparatus for interpolating X-ray tomographic image data by using a machine learning model. A method of interpolating an X-ray tomographic image or X-ray tomographic composite image data includes obtaining a trained model parameter via machine learning that uses a sub-sampled sinogram for learning as an input and uses a full-sampled sinogram for learning as a ground truth; radiating X-rays onto an object at a plurality of preset angular locations via an X-ray source, and obtaining a sparsely-sampled sinogram including X-ray projection data obtained via X-rays detected at the plurality of preset angular locations; applying the trained model parameter to the sparsely-sampled sinogram by using the machine learning model; and generating a densely-sampled sinogram by estimating X-ray projection data not obtained with respect to the object on the sparsely-sampled sinogram.

Claim (Index 13):
The apparatus of  claim 12 , wherein the at least one processor is further configured to cause the following to be performed:\n interpolating the sparsely-sampled sinogram via linear interpolation before applying the trained model parameter to the sparsely-sampled sinogram.

Metadata:
- Claim Count in Document: 2.0
- Percentile: 98.0
- Lexical Diversity: 2.1875
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['12671776', '13057063', '15200435', '15325497', '14997365']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3325874355246005
- 35 USC 102 Novelty (BERT): 0.5137535354767511
- Combined Prediction Score: 0.3507040455198156
- Mean Citation Score: 245.224876
- Max Citation Score: 263.14578
- Similarity Product: 179.78229527747155

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

Dataset: test