Organoids revealed:morphological analysis of the profound next generation in-vitro model with artificial intelligence

作     者：Xuan Du Zaozao Chen Qiwei Li Sheng Yang Lincao Jiang Yi Yang Yanhui Li Zhongze Gu Xuan Du;Zaozao Chen;Qiwei Li;Sheng Yang;Lincao Jiang;Yi Yang;Yanhui Li;Zhongze Gu

作者机构：State Key Laboratory of BioelectronicsSchool of Biological Science and Medical EngineeringSoutheast UniversityNanjing 210096China State Key Laboratory for Novel Software TechnologyNanjing UniversityNanjing 210008China Key Laboratory of Environmental Medicine EngineeringMinistry of EducationSchool of Public HealthSoutheast UniversityNanjing 210009China 

基　　金：the National Key R&D Program of China(No.2017YFA0700500) the National Natural Science Foundation of China(No.62172202) the Experiment Project of ChinaManned Space Program(No.HYZHXM01019) the Fundamental Research Funds for the Central Universities from Southeast University(No.3207032101C3) 

出 版 物：《Bio-Design and Manufacturing》 (生物设计与制造（英文）)

年 卷 期：2023年第6卷第3期

页      码：319-339页

摘      要：In modern terminology,“organoids”refer to cells that grow in a specific three-dimensional(3D)environment in vitro,sharing similar structures with their source organs or *** themorphology or growth characteristics of organoids through a microscope is a commonly used method of organoid ***,it is difficult,time-consuming,and inaccurate to screen and analyze organoids only manually,a problem which cannot be easily solved with traditional *** intelligence(AI)technology has proven to be effective in many biological and medical research fields,especially in the analysis of single-cell or hematoxylin/eosin stained tissue *** used to analyze organoids,AI should also provide more efficient,quantitative,accurate,and fast *** this review,we will first briefly outline the application areas of organoids and then discuss the shortcomings of traditional organoid measurement and analysis ***,we will summarize the development from machine learning to deep learning and the advantages of the latter,and then describe how to utilize a convolutional neural network to solve the challenges in organoid observation and ***,we will discuss the limitations of current AI used in organoid research,as well as opportunities and future research directions.

主 题 词：Artificial intelligence Organoids Morphology Growth characteristics Deep learning Convolutional neural network 

学科分类：0710[理学-生物科学类] 0831[工学-公安技术类] 12[管理学] 1201[管理学-管理科学与工程类] 081104[081104] 08[工学] 0835[0835] 0836[0836] 0811[工学-水利类] 0812[工学-测绘类] 

核心收录：

D　O　I：10.1007/s42242-022-00226-y

馆 藏 号：203118217...