PATENT CLAIM ANALYSIS

Application Number: 15879732
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2018-08
Patent Classification: ["382", "158000"]

Abstract:
Systems and methods for automated segmentation of anatomical structures (e.g., heart). Convolutional neural networks (CNNs) may be employed to autonomously segment parts of an anatomical structure represented by image data, such as 3D MRI data. The CNN utilizes two paths, a contracting path and an expanding path. In at least some implementations, the expanding path includes fewer convolution operations than the contracting path. Systems and methods also autonomously calculate an image intensity threshold that differentiates blood from papillary and trabeculae muscles in the interior of an endocardium contour, and autonomously apply the image intensity threshold to define a contour or mask that describes the boundary of the papillary and trabeculae muscles. Systems and methods also calculate contours or masks delineating the endocardium and epicardium using the trained CNN model, and anatomically localize pathologies or functional characteristics of the myocardial muscle using the calculated contours or masks.

Claim (Index 2):
The machine learning system of  claim 1  wherein the CNN model comprises a contracting path and an expanding path, the contracting path includes a number of convolutional layers and a number of pooling layers, each pooling layer preceded by at least one convolutional layer, and the expanding path includes a number of convolutional layers and a number of upsampling layers, each upsampling layer preceded by at least one convolutional layer and comprises a transpose convolution operation which performs upsampling and interpolation with a learned kernel.

Metadata:
- Claim Count in Document: 40.0
- Percentile: 86.0
- Lexical Diversity: 1.76087
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15294207', '14929806', '12228911', '10150613', '10356455']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3040944871433458
- 35 USC 102 Novelty (BERT): 0.5120087487996229
- Combined Prediction Score: 0.3248859133089735
- Mean Citation Score: 212.206556
- Max Citation Score: 227.47224
- Similarity Product: 141.8923112249565

Labels:
- Claim Label 101: 0
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 0

Dataset: test