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Open-source AICSImageIO library, developed for cell biologists, faithfully converts proprietary microscope image files into an open format
2 min read
In the cell biology research world, there’s been a recent explosion of newer, faster, better resolution microscopes.
But with these technological advances comes a logistics problem for the microscopes’ users: the image files themselves, or more specifically, the file formats. Nearly every microscope brand generates a different kind of image file format, and that can make it difficult for computational biologists who want to analyze or compare images obtained in different formats.
Image files commonly used outside the cell biology world (jpegs, tiffs, pngs) have such conversion software – known as image libraries – available in spades. “But in the scientific community, you have a specific library for reading one format, and then a totally different library for another format,” said Jackson Brown, an engineer at the Allen Institute for Cell Science, a division of the Allen Institute.
Researchers at the Allen Institute for Cell Science use several different kinds of microscopes in their work. They were looking for a way to easily convert all their image files to the Open Microscopy Environment format, or OME, a format developed by a consortium of researchers and software developers that makes open-access, open-source tools for microscopy image data. Programs that convert image files to OME existed, but the Allen Institute teams wanted a program that was more of a one-stop-shop for easily working with any kind of image file.
The software Brown and his colleagues developed, called AICSImageIO, is an open-source microscopy image reading, writing and file conversion library written in Python. It can convert several types of microscopy image files – at any size – to OME or PNG files, enabling cell biologists to more easily analyze and compare microscopy images taken on different machines.
The software ports the image data and its metadata, the technical information associated with an image that’s not directly contained in its pixels, and converts them both faithfully. That includes very high-resolution images and 3D volumetric images too large to fit into any single computer’s memory, including those from the Institute’s lattice light-sheet microscope which can reach 200 GB in a single 3D image – about the size of 25 HD feature-length movies.
The software itself doesn’t display images, but it can sync up with other image viewing software. Currently, the team is working with the open-source image viewer napari and are planning to make the image-viewing step through that program even more seamless in the next iteration of AICSImageIO.
Aside from Brown, Allen Institute for Cell Science engineers Dan Toloudis and Jamie Sherman, Ph.D., are developers on the software.