PATENT CLAIM ANALYSIS

Application Number: 15947558
Application Type: Utility
Filing Date: 2018-04
Publication Date: 2018-10
Patent Classification: ["324", "307000"]

Abstract:
Methods for magnetic resonance fingerprinting (“MRF”) that are more robust to patient motion than conventional MRF techniques are described. The methods described in the present disclosure provide an image reconstruction algorithm for MRF that decreases the motion sensitivity of MRF.

Claim (Index 1):
A method for producing images of a subject with a magnetic resonance imaging (MRI) system, the steps of the methods comprising:\n (a) providing magnetic resonance data to a computer system, wherein the magnetic resonance data were acquired from a subject with an MRI system by acquiring the magnetic resonance data in a series of variable sequence blocks to cause one or more resonant species in the subject to simultaneously produce individual magnetic resonance signals and wherein at least one member of the series of variable sequence blocks differs from at least one other member of the series of variable sequence blocks in at least two sequence block parameters; (b) generating a series of initial image frames with the computer system by comparing the magnetic resonance data to a dictionary of signal evolutions; (c) identifying motion corrupted image frames in the series of initial image frames using the computer system; (d) estimating subject motion from the identified motion corrupted image frames using the computer system; (e) producing motion-compensated magnetic resonance data with the computer system by applying the estimated subject motion to the provided magnetic resonance data; and (f) generating a series of motion-compensated image frames with the computer system by comparing the motion-compensated magnetic resonance data to the dictionary of signal evolutions.

Metadata:
- Claim Count in Document: 11.0
- Percentile: 91.0
- Lexical Diversity: 1.27778
- Patent Class: 324.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15946922', '15945594', '14711815', '15117337', '15589295']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5813942319173754
- 35 USC 102 Novelty (BERT): 0.488149871388358
- Combined Prediction Score: 0.5720697958644737
- Mean Citation Score: 253.74027
- Max Citation Score: 275.16998
- Similarity Product: 238.1250033693672

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