PATENT CLAIM ANALYSIS

Application Number: 15868062
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2018-08
Patent Classification: ["382", "131000"]

Abstract:
Methods and apparatus for automated medical image analysis using deep learning networks are disclosed. In a method of automatically performing a medical image analysis task on a medical image of a patient, a medical image of a patient is received. The medical image is input to a trained deep neural network. An output model that provides a result of a target medical image analysis task on the input medical image is automatically estimated using the trained deep neural network. The trained deep neural network is trained in one of a discriminative adversarial network or a deep image-to-image dual inverse network.

Claim (Index 4):
The method of  claim 3 , wherein the minimax objective function further includes a third cost term computed using a cost function that calculates an error between the ground truth output models and the estimated output models estimated by the estimator network from the input training images.

Metadata:
- Claim Count in Document: 11.0
- Percentile: 86.0
- Lexical Diversity: 2.12
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15382414', '15618384', '14709536', '14706108', '15055161']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3511605441682783
- 35 USC 102 Novelty (BERT): 0.5290767496500396
- Combined Prediction Score: 0.3689521647164545
- Mean Citation Score: 294.73993200000007
- Max Citation Score: 334.34225
- Similarity Product: 256.17526593409474

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