A FRAMEWORK FOR IMAGE BASED UNSUPERVISED CELL CLUSTERING AND SORTING

A framework that includes a feature extractor and a cluster component for clustering is described herein. The framework supports (1) offline image-based unsupervised clustering that replaces time-consuming manual gating; (2) online image-based single cell sorting. During training, one or multiple ce...

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Main Authors LIU, Ming-Chang, CHIANG, Su-Hui
Format Patent
LanguageEnglish
French
German
Published 23.08.2023
Subjects
CALCULATING
COMPUTING
COUNTING
INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES
MEASURING
PHYSICS
TESTING
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Abstract A framework that includes a feature extractor and a cluster component for clustering is described herein. The framework supports (1) offline image-based unsupervised clustering that replaces time-consuming manual gating; (2) online image-based single cell sorting. During training, one or multiple cell image datasets with or without ground truth are used to train feature extractor, which is based on a neural network including several convolutional layers. Once trained, the feature extractor is used to extract features of cell images for unsupervised cell clustering and sorting. In addition, additional datasets may be used to further refine the feature extractor after it has been trained.
AbstractList A framework that includes a feature extractor and a cluster component for clustering is described herein. The framework supports (1) offline image-based unsupervised clustering that replaces time-consuming manual gating; (2) online image-based single cell sorting. During training, one or multiple cell image datasets with or without ground truth are used to train feature extractor, which is based on a neural network including several convolutional layers. Once trained, the feature extractor is used to extract features of cell images for unsupervised cell clustering and sorting. In addition, additional datasets may be used to further refine the feature extractor after it has been trained.
Author LIU, Ming-Chang
CHIANG, Su-Hui
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DocumentTitleAlternate RAHMEN FÜR BILDBASIERTES UNÜBERWACHTES ZELLCLUSTERING UND -SORTIEREN
OSSATURE POUR LE REGROUPEMENT ET LE TRI DE CELLULES NON SUPERVISÉS BASÉS SUR DES IMAGES
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Snippet A framework that includes a feature extractor and a cluster component for clustering is described herein. The framework supports (1) offline image-based...
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SubjectTerms CALCULATING
COMPUTING
COUNTING
INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES
MEASURING
PHYSICS
TESTING
Title A FRAMEWORK FOR IMAGE BASED UNSUPERVISED CELL CLUSTERING AND SORTING
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