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 15):
The system according to  claim 11 , wherein when the liver tissue information is a CT image of the liver tissue or an MRI image of the liver tissue, the processor is further configured to:\n extract, from the CT image of the liver tissue or the MRI image of the liver tissue, a binary image of skin and a binary image of bones using an image segmentation method; calculate a center of mass of the binary image of bones; and calculate a point on the binary image of skin which is nearest to the center of mass; partition the CT image of the liver tissue or the MRI image of the liver tissue into four quadrants according to the center of mass and the point nearest to the center of mass; fit each rib point in a second quadrant to obtain a rib fitted curve; and move the rib fitted curve towards a first quadrant by a predefined value to obtain a boundary region curve; and determine a region between the boundary region curve and the rib fitted curve as a boundary region of the liver tissue.

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): 0.3378720469120406
- 35 USC 102 Novelty (BERT): 0.5468114873880875
- Combined Prediction Score: 0.3587659909596453
- Mean Citation Score: 203.84184
- Max Citation Score: 396.77808
- Similarity Product: 316.0297546853256

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