Redirigiendo al acceso original de articulo en 16 segundos...
Inicio  /  Applied Sciences  /  Vol: 13 Par: 2 (2023)  /  Artículo
ARTÍCULO
TITULO

Image Processing Approach for Grading IVF Blastocyst: A State-of-the-Art Review and Future Perspective of Deep Learning-Based Models

Iza Sazanita Isa    
Umi Kalsom Yusof and Murizah Mohd Zain    

Resumen

The development of intelligence-based methods and application systems has expanded for the use of quality blastocyst selection in in vitro fertilization (IVF). Significant models on assisted reproductive technology (ART) have been discovered, including ones that process morphological image approaches and extract attributes of blastocyst quality. In this study, (1) the state-of-the-art in ART is established using an automated deep learning approach, applications for grading blastocysts in IVF, and related image processing techniques. (2) Thirty final publications in IVF and deep learning were found by an extensive literature search from databases using several relevant sets of keywords based on papers published in full-text English articles between 2012 and 2022. This scoping review sparks fresh thought in deep learning-based automated blastocyst grading. (3) This scoping review introduces a novel notion in the realm of automated blastocyst grading utilizing deep learning applications, showing that these automated methods can frequently match or even outperform skilled embryologists in particular deep learning tasks. This review adds to our understanding of the procedure for selecting embryos that are suitable for implantation and offers important data for the creation of an automated computer-based system for grading blastocysts that applies deep learning.

 Artículos similares

       
 
Chih-Yung Chen, Shang-Feng Lin, Yuan-Wei Tseng, Zhe-Wei Dong and Cheng-Han Cai    
Remote coffee grinder burr wear level assessment system.
Revista: Applied Sciences

 
Tianhao Gao, Meng Zhang, Yifan Zhu, Youjian Zhang, Xiangsheng Pang, Jing Ying and Wenming Liu    
Classifying sports videos is complex due to their dynamic nature. Traditional methods, like optical flow and the Histogram of Oriented Gradient (HOG), are limited by their need for expertise and lack of universality. Deep learning, particularly Convoluti... ver más
Revista: Applied Sciences

 
Yongzhen Zhang, Yanbo Hui, Ying Zhou, Juanjuan Liu, Ju Gao, Xiaoliang Wang, Baiwei Wang, Mengqi Xie and Haonan Hou    
Moldy corn produces aflatoxin and gibberellin, which can have adverse effects on human health if consumed. Mold is a significant factor that affects the safe storage of corn. If not detected and controlled in a timely manner, it will result in substantia... ver más
Revista: Applied Sciences

 
Hui-Jun Kim, Jung-Soon Kim and Sung-Hee Kim    
The existing question-and-answer screening test has a limitation in that test accuracy varies due to a high learning effect and based on the inspector?s competency, which can have consequences for rapid-onset cognitive-related diseases. To solve this pro... ver más
Revista: Applied Sciences

 
Ahad Alotaibi, Chris Chatwin and Phil Birch    
In aerial surveillance systems, achieving optimal object detection precision is of paramount importance for effective monitoring and reconnaissance. This article presents a novel approach to enhance object detection accuracy through the integration of De... ver más