PATENT CLAIM ANALYSIS

Application Number: 16379248
Application Type: Utility
Filing Date: 2019-04
Publication Date: 2019-10
Patent Classification: ["382", "128000"]

Abstract:
Methods and systems are described for assessing a vessel obstruction. The methods and systems obtain a volumetric image dataset for a target organ that includes a vessel of interest, extract an axial trajectory extending along of a vessel of interest (VOI) within the volumetric image dataset, and create a three-dimensional (3D) multi-planer reformatted (MPR) image based on the volumetric image dataset and the axial trajectory of the VOI. The methods and systems also extract a VOI parameter from the MPR utilizing a machine learning-based vessel obstruction assessment (VOA) model. Methods and systems are also described for implementing a prediction phase to perform at least one of i) detecting plaque type, ii) classifying anatomical severity of vessel blockage, and/or iii) classifying a hemodynamic severity of vessel obstructions within an unseen portion of the volumetric image data set.

Claim (Index 6):
The method of  claim 3 , wherein:\n a size of the cube is defined to contain a whole lumen for the VOI and a portion of tissue outside of the lumen to facilitate extracting the VOI parameter in connection with positive remodeling, wherein positive remodeling refers to a direction of atherosclerotic plaque growth.

Metadata:
- Claim Count in Document: 54.0
- Percentile: 100.0
- Lexical Diversity: 2.01299
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15933854', '16241165', '14011151', '14684529', '15958483']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4135423928190986
- 35 USC 102 Novelty (BERT): 0.5510864526897096
- Combined Prediction Score: 0.4272967988061598
- Mean Citation Score: 350.92807000000005
- Max Citation Score: 433.42197
- Similarity Product: 300.8167826942736

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