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

Cell Rep Methods. 2023 Jun 26;3(7):100517. doi: 10.1016/j.crmeth.2023.100517. eCollection 2023 Jul 24.

Abstract

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 programming skills with state-of-the-art deep-learning algorithms for segmentation, object detection, and classification. 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.

Keywords: classification; deep learning; image analysis; microscopy; object detection; segmentation; tracking.

MeSH terms

  • Algorithms
  • Deep Learning*
  • Image Processing, Computer-Assisted / methods
  • Software