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 3):
The method of  claim 2 , further comprising associating a locator on a selected location of said biological structure, such that when the at least one biological structure is selected in the test image, the locator appears centered or substantially centered with respect to the selected location on a display device.

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): 0.3342310269306592
- 35 USC 102 Novelty (BERT): 0.540116783904338
- Combined Prediction Score: 0.3548196026280271
- Mean Citation Score: 244.44436000000005
- Max Citation Score: 400.0838
- Similarity Product: 245.4856788458944

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