Kanakasabapathy et al., 2019 - Google Patents

Development and evaluation of inexpensive automated deep learning-based imaging systems for embryology

Kanakasabapathy et al., 2019

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Document ID
11642114192871159449
Author
Kanakasabapathy M
Thirumalaraju P
Bormann C
Kandula H
Dimitriadis I
Souter I
Yogesh V
Pavan S
Yarravarapu D
Gupta R
Pooniwala R
Shafiee H
Publication year
Publication venue
Lab on a Chip

External Links

Snippet

Embryo assessment and selection is a critical step in an in vitro fertilization (IVF) procedure. Current embryo assessment approaches such as manual microscopy analysis done by embryologists or semi-automated time-lapse imaging systems are highly subjective, time …
Continue reading at www.ncbi.nlm.nih.gov (HTML) (other versions)

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume, or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N15/14—Electro-optical investigation, e.g. flow cytometers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by the preceding groups
    • G01N33/48—Investigating or analysing materials by specific methods not covered by the preceding groups biological material, e.g. blood, urine; Haemocytometers

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