PATENT CLAIM ANALYSIS

Application Number: 16155943
Application Type: Utility
Filing Date: 2018-10
Publication Date: 2019-02
Patent Classification: ["382", "131000"]

Abstract:
Presented herein are efficient and reliable systems and methods for calculating and extracting three-dimensional central axes of bones of animal subjects—for example, animal subjects scanned by in vivo or ex vivo microCT platforms—to capture both the general and localized tangential directions of the bone, along with its shape, form, curvature, and orientation. With bone detection and segmentation algorithms, the skeletal bones of animal subjects scanned by CT or microCT scanners can be detected, segmented, and visualized. Three dimensional central axes determined using these methods provide important information about the skeletal bones.

Claim (Index 7):
The method of  claim 5 , wherein filling borders of the bone of interest further comprises:\n representing image data from the binary bone mask of the bone of interest digitally as one or more data-cubes; identifying a vertex of a data-cube, the vertex having all edges connected to the vertex associated with true voxels; forming a 2-D image from the three faces connected to the identified vertex of the data-cube; filling morphological holes in the thusly formed 2-D image to produce a filled surface; and mapping the filled surface back to the three faces connected to the identified vertex of the data-cube.

Metadata:
- Claim Count in Document: 16.0
- Percentile: 97.0
- Lexical Diversity: 1.54545
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15081788', '14812483', '15985070', '11036439', '12624519']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3669014691385029
- 35 USC 102 Novelty (BERT): 0.5819324464240627
- Combined Prediction Score: 0.3884045668670589
- Mean Citation Score: 278.036962
- Max Citation Score: 497.96326
- Similarity Product: 416.90919985788696

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