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Artificial Intelligence in Label-free Microscopy

von , 2017 bei Springer

Kategorien: Computergraphik, Medizin, Anatomie & Physiologie, Elektronik, Maschinenbau

Verlag

Springer

ISBN E-Book

978-3-319-51448-2

ISBN Printausgabe

978-3-319-51447-5

Format

E-Book

Datum der Veröffentlichung

April 2017

Sprache

Englisch

Bewertungen

(noch nicht bewertet)

Aufrufe

39

This book introduces time-stretch quantitative phase imaging (TS-QPI), a high-throughput label-free imaging flow cytometer developed for big data acquisition and analysis in phenotypic screening. TS-QPI is able to capture quantitative optical phase and intensity images simultaneously, enabling high-content cell analysis, cancer diagnostics, personalized genomics, and drug development. The authors also demonstrate a complete machine learning pipeline that performs optical phase measurement, image processing, feature extraction, and classification, enabling high-throughput quantitative imaging that achieves record high accuracy in label -free cellular phenotypic screening and opens up a new path to data-driven diagnosis.

Komponente 1

Komponente 2

Komponente 3 (Verfügbar nach Kauf / Miete)

Komponente 4 (Verfügbar nach Kauf / Miete)

Komponente 5 (Verfügbar nach Kauf / Miete)

Komponente 6 (Verfügbar nach Kauf / Miete)

Komponente 7 (Verfügbar nach Kauf / Miete)

Komponente 8 (Verfügbar nach Kauf / Miete)

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The goal of this volume is to summarize the state-of-the-art in the utilization of computer vision techniques in the diagnosis of skin cancer.
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