Development and evaluation of inexpensive automated deep learning-based imaging systems for embryology-Reference-Cited by-同舟云学术

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

Published:2019 Issue:24 Volume:19 Page:4139-4145
ISSN:1473-0197
Container-title:Lab on a Chip
language:en
Short-container-title:Lab Chip

Author:

Kanakasabapathy Manoj Kumar¹²³⁴⁵^ORCID,Thirumalaraju Prudhvi¹²³⁴⁵,Bormann Charles L.⁶⁷⁸⁴⁵,Kandula Hemanth¹²³⁴⁵^ORCID,Dimitriadis Irene⁶⁷⁸⁴⁵,Souter Irene⁶⁷⁸⁴⁵,Yogesh Vinish¹²³⁴⁵,Kota Sai Pavan Sandeep¹²³⁴⁵,Yarravarapu Divyank¹²³⁴⁵^ORCID,Gupta Raghav¹²³⁴⁵,Pooniwala Rohan¹²³⁴⁵,Shafiee Hadi¹²³⁴⁵^ORCID

Affiliation:

1. Division of Engineering in Medicine

2. Department of Medicine

3. Brigham and Women's Hospital

4. Harvard Medical School

5. Boston

6. Division of Reproductive Endocrinology and Infertility

7. Department of Obstetrics and Gynaecology

8. Massachusetts General Hospital

Abstract

Artificial intelligence enabled inexpensive imaging hardware can be a valuable tool for reliable embryo assessments in in vitro fertilization.

Funder

National Institutes of Health

Brigham and Women's Hospital

Massachusetts General Hospital

Publisher

Royal Society of Chemistry (RSC)

Subject

Biomedical Engineering,General Chemistry,Biochemistry,Bioengineering

Link

http://pubs.rsc.org/en/content/articlepdf/2019/LC/C9LC00721K

Reference33 articles.

1. P. Turchi , in Clinical Management of Male Infertility , ed. G. Cavallini and G. Beretta , Springer International Publishing , Cham , 2015 , pp. 5–11 , 10.1007/978-3-319-08503-6_2

2. National, Regional, and Global Trends in Infertility Prevalence Since 1990: A Systematic Analysis of 277 Health Surveys

3. 'Cheaper than a newcomer': on the social production of IVF policy in Israel

4. Progress we can be proud of: U.S. trends in assisted reproduction over the first 20 years1 1Reprints are not available.

5. CDC, Fertility Clinic Success Rates Report, 2015

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