D-CryptO: deep learning-based analysis of colon organoid morphology from brightfield images-Reference-Cited by-同舟云学术

D-CryptO: deep learning-based analysis of colon organoid morphology from brightfield images

Published:2022 Issue:21 Volume:22 Page:4118-4128
ISSN:1473-0197
Container-title:Lab on a Chip
language:en
Short-container-title:Lab Chip

Author:

Abdul Lyan¹,Xu Jocelyn²,Sotra Alexander¹,Chaudary Abbas³,Gao Jerry⁴,Rajasekar Shravanthi³^ORCID,Anvari Nicky¹,Mahyar Hamidreza⁵,Zhang Boyang¹³^ORCID

Affiliation:

1. School of Biomedical Engineering, McMaster University, 1280 Main Street West, Hamilton, ON, L8S 4L8, Canada

2. Faculty of Engineering, McMaster University, 1280 Main Street West, Hamilton, ON, L8S 4L8, Canada

3. Department of Chemical Engineering, McMaster University, 1280 Main Street West, Hamilton, ON, L8S 4L8, Canada

4. Faculty of Science, McGill University, 845 Sherbrooke Street West, Montreal, QC H3A 0G4, Canada

5. W Booth School of Engineering Practice and Technology, McMaster University, 1280 Main Street West, Hamilton, ON, L8S 4L8, Canada

Abstract

D-CryptO is a deep learning-based tool that can be used to analyze colon organoid structural maturity directly from brightfield images. D-CryptO can be applied in many cases such as analyzing organoids following chemotherapeutic drug treatment.

Funder

Natural Sciences and Engineering Research Council of Canada

Canadian Institutes of Health Research

Publisher

Royal Society of Chemistry (RSC)

Subject

Biomedical Engineering,General Chemistry,Biochemistry,Bioengineering

Link

http://pubs.rsc.org/en/content/articlepdf/2022/LC/D2LC00596D

Reference32 articles.

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3. Cell fate coordinates mechano-osmotic forces in intestinal crypt formation

4. Colonic organoids derived from human induced pluripotent stem cells for modeling colorectal cancer and drug testing

5. Generation of human colonic organoids from human pluripotent stem cells

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