MIA is an open-source standalone deep learning application for microscopic image analysis

被引:3
|
作者
Koerber, Nils [1 ,2 ]
机构
[1] German Fed Inst Risk Assessment BfR, German Ctr Protect Lab Anim Bf3R, Berlin, Germany
[2] Robert Koch Inst, Ctr Artificial Intelligence Publ Hlth Res, Berlin, Germany
来源
CELL REPORTS METHODS | 2023年 / 3卷 / 07期
关键词
PLATFORM;
D O I
10.1016/j.crmeth.2023.100517
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
In recent years, the amount of data generated by imaging techniques has grown rapidly, along with increasing computational power and the development of deep learning algorithms. To address the need for powerful automated image analysis tools for a broad range of applications in the biomedical sciences, the Microscopic Image Analyzer (MIA) was developed. MIA combines a graphical user interface that obviates the need for pro-gramming skills with state-of-the-art deep-learning algorithms for segmentation, object detection, and clas-sification. It runs as a standalone, platform-independent application and uses open data formats, which are compatible with commonly used open-source software packages. The software provides a unified interface for easy image labeling, model training, and inference. Furthermore, the software was evaluated in a public competition and performed among the top three for all tested datasets.
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页数:11
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