PATENT CLAIM ANALYSIS

Application Number: 16097653
Application Type: Utility
Filing Date: 2018-10
Publication Date: 2019-05
Patent Classification: ["382", "128000"]

Abstract:
A system and method are provided for enabling atlas registration in medical imaging, said atlas registration comprising matching a medical atlas  300, 302  to a medical image  320 . The system and method may execute a Reinforcement Learning (RL) algorithm to learn a model for matching the medical atlas to the medical image, wherein said learning is on the basis of a reward function quantifying a degree of match between the medical atlas and the medical image. The state space of the RL algorithm may be determined on the basis of a set of features extracted from i) the atlas data and ii) the image data. As such, a model is obtained for medical atlas registration without the use, or with a reduced use, of heuristics. By using a machine learning based approach, the solution can easily be applied to different atlas matching problems, e.g., to different types of medical atlases and/or medical images.

Claim (Index 12):
A method of enabling atlas registration in medical imaging, said atlas registration comprising matching a medical atlas to a medical image, comprising:\n accessing atlas data defining the medical atlas; accessing image data of the medical image; executing a Reinforcement Learning algorithm to learn a model for matching the medical atlas to the medical image, wherein said learning is on the basis of a reward function quantifying a degree of match between the medical atlas and the medical image; determining a state space for the Reinforcement Learning algorithm on the basis of a set of features extracted from i) the atlas data and ii) the image data; and determining an action space for the Reinforcement Learning algorithm on the basis of a predefined set of transformation actions which are available to be applied to the medical atlas, wherein the action space is structured into different levels, wherein each of the different levels comprises a subset of the transformation actions, and wherein the different levels form a hierarchy of transformation actions in which selection of a sequence of transformation actions by the Reinforcement Learning algorithm is restricted to a downward progression in the hierarchy.

Metadata:
- Claim Count in Document: 27.0
- Percentile: 97.0
- Lexical Diversity: 2.03571
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['15224710', '15689411', '15160699', '15386856', '15397638']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3217829233588219
- 35 USC 102 Novelty (BERT): 0.4725631172068087
- Combined Prediction Score: 0.3368609427436206
- Mean Citation Score: 193.94943
- Max Citation Score: 199.92468
- Similarity Product: 161.28860392337322

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

Dataset: test