PATENT CLAIM ANALYSIS

Application Number: 16417529
Application Type: Utility
Filing Date: 2019-05
Publication Date: 2019-09
Patent Classification: ["382", "131000"]

Abstract:
The present disclosure relates to the technical field of medical image processing and, in particular, to a liver boundary identification method and a system. The method includes: obtaining liver tissue information of a liver tissue to be identified; identifying a liver tissue boundary in the liver tissue information according to a feature of the liver tissue corresponding to the liver tissue information and a feature of the liver tissue boundary corresponding to the liver tissue information using an image processing technology or a signal processing technology; and outputting position information of the identified liver tissue boundary. By using the disclosed method, the liver tissue boundary can be identified automatically, the efficiency of identifying the liver boundary can be improved, and automatic positioning of the liver boundary can thus be achieved.

Claim (Index 4):
The method according to  claim 2 , wherein, when the liver tissue information is a two-dimensional ultrasonic image of the liver tissue,\n partitioning the liver tissue information into a plurality of detection sub-regions comprises: partitioning the two-dimensional ultrasonic image of the liver tissue into a plurality of rectangular detection sub-regions R ij , i and j being natural numbers; calculating a feature value of the liver tissue information in each of the detection sub-regions, and determining the liver tissue boundary according to the feature value of the liver tissue information in the detection sub-regions comprises: calculating a weight W kj  of each detection sub-region R kj  according to the following formula, and determining the detection sub-region corresponding to a maximum weight value to be a boundary region of the liver tissue: W kj = M kj SD kj * d kj where M kj  is an average gray value of the two-dimensional ultrasonic image of the liver tissue in the detection sub-region R kj , SD kj  is standard deviation of grayscale of the two-dimensional ultrasonic image of the liver tissue in the detection sub-region R kj , d kj  is scanning depth corresponding to the detection sub-region R kj , k=i max /2 and is a natural number, and i max  is a maximum value in a value range of i.

Metadata:
- Claim Count in Document: 11.0
- Percentile: 100.0
- Lexical Diversity: 2.71154
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['15487032', '12651562', '12986414', '12213046', '13343053']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3354750572935404
- 35 USC 102 Novelty (BERT): 0.5500018848188071
- Combined Prediction Score: 0.356927740046067
- Mean Citation Score: 203.84184
- Max Citation Score: 396.77808
- Similarity Product: 382.1770853317165

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