PATENT CLAIM ANALYSIS

Application Number: 16161796
Application Type: Utility
Filing Date: 2018-10
Publication Date: 2019-02
Patent Classification: ["382", "156000"]

Abstract:
The present disclosure relates to systems, methods, devices, and non-transitory computer-readable storage medium for segmenting three-dimensional images. In one implementation, a computer-implemented method for segmenting a three-dimensional image is provided. The method may include receiving the three-dimensional image acquired by an imaging device, and creating a first stack of two-dimensional images from a first plane of the three-dimensional image and a second stack of two-dimensional images from a second plane of the three-dimensional image. The method may further include segmenting, by a processor, the first stack and the second stack of two-dimensional images using at least one neural network model. The method may also include determining, by the processor, a label map for the three-dimensional image by aggregating the segmentation results from the first stack and second stack.

Claim (Index 7):
The method of  claim 1 , wherein the machine learning model comprises a deep convolutional neural network model.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 97.0
- Lexical Diversity: 2.36667
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15935077', '15248628', '15248490', '15385732', '14474407']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3624388559108291
- 35 USC 102 Novelty (BERT): 0.5453924290905208
- Combined Prediction Score: 0.3807342132287983
- Mean Citation Score: 331.30351
- Max Citation Score: 384.01437
- Similarity Product: 329.16568362498884

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

Dataset: test