A robust deep learning-based multiclass segmentation method for analyzing human metaphase II oocyte images-Reference-Cited by-同舟云学术

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A robust deep learning-based multiclass segmentation method for analyzing human metaphase II oocyte images

Published:2021-04 Issue: Volume:201 Page:105946
ISSN:0169-2607
Container-title:Computer Methods and Programs in Biomedicine
language:en
Short-container-title:Computer Methods and Programs in Biomedicine

Author:

Firuzinia Sedighe,Afzali Seyed Mahmoodreza,Ghasemian Fatemeh,Mirroshandel Seyed Abolghasem

Funder

Guilan University of Medical Sciences

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications,Software

Reference39 articles.

1. Pregnancies after intracytoplasmic injection of single spermatozoon into an oocyte;Palermo;Lancet North Am. Ed.,1992

2. High fertilization and implantation rates after intracytoplasmic sperm injection;Van Steirteghem;Hum. Reprod.,1993

3. Evaluating the value of day 0 of an ICSI cycle on indicating laboratory outcome;Maziotis;Sci. Rep.,2020

4. Assessment of embryo viability in assisted reproductive technology: shortcomings of current approaches and the emerging role of metabolomics;Bromer;Curr. Opin. Obstet. Gynecol.,2008

5. Computer-assisted oocyte morphometry before ICSI: correlation of oocyte measurements with fertilization and embryo development;Camargos;Reprod. Sci.,2012

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1. An artificial intelligence tool predicts blastocyst development from static images of fresh mature oocytes;Reproductive BioMedicine Online;2024-06

2. Testing the generalizability and effectiveness of deep learning models among clinics: sperm detection as a pilot study;Reproductive Biology and Endocrinology;2024-05-22

3. Segmentation of mature human oocytes provides interpretable and improved blastocyst outcome predictions by a machine learning model;Scientific Reports;2024-05-08

4. Current applications of artificial intelligence in assisted reproductive technologies through the perspective of a patient's journey;Current Opinion in Obstetrics & Gynecology;2024-04-01

5. Bioengineering: a promising approach for standardization and automation of assisted reproductive technology;F&S Reviews;2024-01

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