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 12):
A method to train a vessel obstruction assessment (VOA) model, comprising:\n obtaining a training database that includes volumetric imaging datasets for multiple patients and corresponding coronary artery disease (CAD) related reference values, the volumetric image data sets being for a target organ that includes a vessel of interest, the CAD related reference values corresponding to one or more points along a vessel of interest within the corresponding imaging data set; and for at least a portion of the volumetric image data sets and corresponding CAD related reference values,\n extracting an axial trajectory extending along of a vessel of interest (VOI) within the corresponding volumetric image dataset, \n creating a three-dimensional (3D) multi-planer reformatted (MPR) image based on the corresponding volumetric image dataset and the axial trajectory of the VOI, the MPR image extending along the axial trajectory of the VOI, and \n training a machine learning-based vessel obstruction assessment (VOA) model based on the MPR images, the training further comprising extracting, from the MPR images, features characterizing a CAD related parameter along the axial trajectory within the VOI.

Metadata:
- Claim Count in Document: 54.0
- Percentile: 100.0
- Lexical Diversity: 2.01299
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15933854', '16241165', '14011151', '14684529', '15958483']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3843749528469916
- 35 USC 102 Novelty (BERT): 0.5501171607546381
- Combined Prediction Score: 0.4009491736377563
- Mean Citation Score: 350.92807000000005
- Max Citation Score: 433.42197
- Similarity Product: 312.77581480844736

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