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Artificial Intelligence in Label-free Microscopy: Biological Cell Classification

Description: A new copy. Pages clean and unmarked. A light diagonal blade scrape on the cover. Otherwise, no cover wear. Images on listing, are of this book. HARDCOVER________________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.

Price: 8 USD

Location: White Bluff, Tennessee

End Time: 2025-01-03T06:09:26.000Z

Shipping Cost: 5.6 USD

Product Images

Artificial Intelligence in Label-free Microscopy: Biological Cell ClassificationArtificial Intelligence in Label-free Microscopy: Biological Cell Classification

Item Specifics

Return shipping will be paid by: Buyer

All returns accepted: Returns Accepted

Item must be returned within: 30 Days

Refund will be given as: Money Back

Book Title: Artificial Intelligence in Label-free Microscopy: Biological Cel

Custom Bundle: No

Book Series: Artificial Intelligence in Label-free Microscopy: Biological Cel

Original Language: English

Item Length: 9.3in.

Vintage: No

Personalize: No

Format: Hardcover

Language: English

Item Height: 1.2in.

Personalized: No

Features: Illustrated, N/A

Topic: Computer Graphics, Electronics / General, Microscopes & Microscopy, Biomedical

Item Width: 6.1in.

Signed: No

Ex Libris: No

Narrative Type: Nonfiction

Publisher: Springer International Publishing A&G

Intended Audience: Young Adults, Adults

Inscribed: No

Edition: Collector's Edition

Publication Year: 2017

Type: SCIENCE, BIOLOGY, LEARNING, HIGHSCHOOL

Literary Movement: Enlightenment, Modernism

Era: 2020s

Author: Ata Mahjoubfar, Bahram Jalali, Claire Lifan Chen

Genre: Technology & Engineering, Computers, Science

Country/Region of Manufacture: United States

Item Weight: 16.7 Oz

Number of Pages: 140 Pages

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