PATENT CLAIM ANALYSIS

Application Number: 15872304
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2019-07
Patent Classification: ["382", "131000"]

Abstract:
A generative network is used for lung lobe segmentation or lung fissure localization, or for training a machine network for lobar segmentation or localization. For segmentation, deep learning is used to better deal with a sparse sampling of training data. To increase the amount of training data available, an image-to-image or generative network localizes fissures in at least some of the samples. The deep-learnt network, fissure localization, or other segmentation may benefit from generative localization of fissures.

Claim (Index 1):
A method for lung lobe segmentation in a medical imaging system, the method comprising:\n scanning, by a medical scanner, lungs of a patient, the scanning providing first imaging data representing the lungs of the patient; applying, by an image processor, a machine-learnt generative network to the first imaging data, the machine-learnt generative network trained to output second imaging data with labeled fissures in response to the applying; segmenting, by the image processor, lobar regions of the lungs represented in the first imaging data based on the labeled fissures and the first imaging data; and outputting, on a display, an image of the lobar regions of the lung of the patient.

Metadata:
- Claim Count in Document: 8.0
- Percentile: 86.0
- Lexical Diversity: 1.7551
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14643935', '11566323', '14518138', '14690391', '13804542']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3475734099569743
- 35 USC 102 Novelty (BERT): 0.4872268017619917
- Combined Prediction Score: 0.361538749137476
- Mean Citation Score: 245.78362800000005
- Max Citation Score: 258.20218
- Similarity Product: 223.20005240920665

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