Method for classifying an input image representing a particle in a sample
AssigneesBioaster, Biomerieux
InventorsPierre MAHÉ, Meriem EL AZAMI, Elodie DEGOUT-CHARMETTE, Zohreh SEDAGHAT, Quentin JOSSO, Fabian ROL
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Abstract
A method for classifying at least one input image representing a target particle in a sample involves implementing, by data processing a client, steps of: (B) extracting a characteristic map of the target particle from the input image; (c) reducing the number of variables in the extracted characteristic map, using the t-SNE algorithm; (d) classifying, unsupervised, the input image based on the characteristic map having a reduced number of variables.
Claims14
A method for classifying at least one input image representing a target particle in a sample, the method being characterized in that it comprises implementation, by data-processing means of a client, of steps of:
- (b) extraction of a feature map of said target particle from the input image;
- (c) reduction of the number of variables of the extracted feature map, by means of the t-SNE algorithm;
- (d) unsupervised classification of said input image depending on said feature map having a reduced number of variables.
A system for classifying at least one input image representing a target particle in a sample comprising at least one client comprising data-processing means, characterized in that said data-processing means are configured to implement:
- extraction of a feature map of said target particle via analysis of the at least one input image;
- reduction of the number of variables of the feature map, by means of the t-SNE algorithm;
- unsupervised classification of said input image depending on said feature map having a reduced number of variables.
Dependencies are inferred from the claim text.