scholarly journals Time-lapse microscopy and image analysis in basic and clinical embryo development research

2013 ◽  
Vol 26 (2) ◽  
pp. 120-129 ◽  
Author(s):  
C. Wong ◽  
A.A. Chen ◽  
B. Behr ◽  
S. Shen
Keyword(s):  
Image Analysis ◽  
Embryo Development ◽  
Time Lapse ◽  
Development Research ◽  
Time Lapse Microscopy

scholarly journals PRESENCE OF ABNORMAL CELL CLEAVAGE, CELL FUSION OR BOTH SEEN DURING EMBRYO DEVELOPMENT ON TIME-LAPSE MICROSCOPY IS NOT PREDICTIVE OF CHROMOSOMAL ANEUPLOIDY

2020 ◽  
Vol 114 (3) ◽  
pp. e44
Author(s):  
Alice J. Shapiro ◽  
Lindsay Kroener ◽  
Nicholas J. Jackson ◽  
Zachary Haimowitz ◽  
Alin Lina Akopians ◽  
...  
Keyword(s):  
Cell Fusion ◽  
Embryo Development ◽  
Time Lapse ◽  
Abnormal Cell ◽  
Time Lapse Microscopy ◽  
Cell Cleavage ◽  
Chromosomal Aneuploidy

Atypical embryo phenotypes identified by time-lapse microscopy: high prevalence and association with embryo development

2014 ◽  
Vol 101 (6) ◽  
pp. 1637-1648.e5 ◽  
Author(s):  
Kelly Athayde Wirka ◽  
Alice A. Chen ◽  
Joe Conaghan ◽  
Kristen Ivani ◽  
Marina Gvakharia ◽  
...  
Keyword(s):  
Embryo Development ◽  
Time Lapse ◽  
Time Lapse Microscopy ◽  
High Prevalence

Evaluation of sperm DNA integrity and its effect on embryo development using time-lapse microscopy

2014 ◽  
Vol 102 (3) ◽  
pp. e312
Author(s):  
T. Lundberg ◽  
F. Hambiliki ◽  
F. Sondèn ◽  
E. Akerlund ◽  
M. Bungum
Keyword(s):  
Embryo Development ◽  
Time Lapse ◽  
Dna Integrity ◽  
Time Lapse Microscopy ◽  
Sperm Dna Integrity ◽  
Sperm Dna

scholarly journals Quantification of Mouse Hematopoietic Progenitors’ Formation Using Time-lapse Microscopy and Image Analysis

BIO-PROTOCOL ◽  
2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Isabelle Bergiers ◽  
Christian Tischer ◽  
Özge Bölükbaşı ◽  
Christophe Lancrin
Keyword(s):  
Image Analysis ◽  
Time Lapse ◽  
Hematopoietic Progenitors ◽  
Time Lapse Microscopy

scholarly journals An Advanced Framework for Time-lapse Microscopy Image Analysis

2020 ◽  
Author(s):  
Qibing Jiang ◽  
Praneeth Sudalagunta ◽  
Mark B. Meads ◽  
Khandakar Tanvir Ahmed ◽  
Tara Rutkowski ◽  
...  
Keyword(s):  
Image Analysis ◽  
Drug Response ◽  
Time Lapse ◽  
Response To Therapy ◽  
Patient Specific ◽  
Microscopy Imaging ◽  
Time Lapse Microscopy ◽  
Link Type ◽  
Microscopy Image ◽  
Microscopy Image Analysis

ABSTRACTTime-lapse microscopy is a powerful technique that generates large volumes of image-based information to quantify the behaviors of cell populations. This method has been applied to cancer studies to estimate the drug response for precision medicine and has great potential to address inter-patient (or intertumoral) heterogeneity. A couple of algorithms exist to analyze time-lapse microscopy images; however, most deal with very high-resolution images involving few cells (typically cell lines). There are currently no advanced and efficient computational frameworks available to process large-scale time-lapse microscopy imaging data to estimate patient-specific response to therapy based on a large population of primary cells. In this paper, we propose a robust and user-friendly pipeline to preprocess the images and track the behaviors of thousands of cancer cells simultaneously for a better drug response prediction of cancer patients.Availability and ImplementationSource code is available at: https://github.com/CompbioLabUCF/CellTrackACM Reference FormatQibing Jiang, Praneeth Sudalagunta, Mark B. Meads, Khandakar Tanvir Ahmed, Tara Rutkowski, Ken Shain, Ariosto S. Silva, and Wei Zhang. 2020. An Advanced Framework for Time-lapse Microscopy Image Analysis. In Proceedings of BioKDD: 19th International Workshop on Data Mining In Bioinformatics (BioKDD). ACM, New York, NY, USA, 8 pages. https://doi.org/10.1145/nnnnnnn.nnnnnnn

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