PATENT CLAIM ANALYSIS

Application Number: 16130945
Application Type: Utility
Filing Date: 2018-09
Publication Date: 2019-01
Patent Classification: ["382", "133000"]

Abstract:
The subject disclosure presents systems and computer-implemented methods for automatic immune cell detection that is of assistance in clinical immune profile studies. The automatic immune cell detection method involves retrieving a plurality of image channels from a multi-channel image such as an RGB image or biologically meaningful unmixed image. A cell detector is trained to identify the immune cells by a convolutional neural network in one or multiple image channels. Further, the automatic immune cell detection algorithm involves utilizing a non-maximum suppression algorithm to obtain the immune cell coordinates from a probability map of immune cell presence possibility generated from the convolutional neural network classifier.

Claim (Index 9):
The method of  claim 8 , further comprising using a local maximum finding method for obtaining cell centroid coordinates for at least one of the biological structures from the probability map.

Metadata:
- Claim Count in Document: 17.0
- Percentile: 97.0
- Lexical Diversity: 1.66667
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15360447', '15365831', '15422343', '15690037', '15910972']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3339049081790078
- 35 USC 102 Novelty (BERT): 0.5405875286701435
- Combined Prediction Score: 0.3545731702281213
- Mean Citation Score: 244.44436000000005
- Max Citation Score: 400.0838
- Similarity Product: 254.14659345998763

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