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 6):
The method of  claim 5 , wherein:\n learning the parameters of the discriminator network to optimize the minimax objective function comprises adjusting the parameters of the discriminator network to maximize probability scores computed by the discriminator network for the ground truth output models and to minimize probability scores computed by the discriminator for the estimated output models estimated by the estimator network from the input training images over the set of training samples; and learning the parameters of the estimator network to optimize the minimax objective function comprises adjusting the parameters of the estimator network to minimize the error between the ground truth output models and estimated output models and estimated by the estimator network and to maximize the probability scores computed by the discriminator for the estimated models estimated by the estimator network over the set of training samples.

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): 0.3511726423787855
- 35 USC 102 Novelty (BERT): 0.5301734571814376
- Combined Prediction Score: 0.3690727238590507
- Mean Citation Score: 294.73993200000007
- Max Citation Score: 334.34225
- Similarity Product: 243.56845156478883

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