View source for 2024Last Ais

== Citation ==

M. G. Last, L. Abendstein, L. M. Voortman, and T. H. Sharp, “Streamlining segmentation of cryo-electron tomography datasets with Ais,” Elife, vol. 13, p. RP98552, 2024.

== Abstract ==

Segmentation is a critical data processing step in many applications of cryo-electron
tomography. Downstream analyses, such as subtomogram averaging, are often based on segmentation
results, and are thus critically dependent on the availability of open-source
software for accurate
as well as high-throughput
tomogram segmentation. There is a need for more user-friendly,
flexible,
and comprehensive segmentation software that offers an insightful overview of all steps involved in
preparing automated segmentations. Here, we present Ais: a dedicated tomogram segmentation
package that is geared towards both high performance and accessibility, available on GitHub. In
this report, we demonstrate two common processing steps that can be greatly accelerated with Ais:
particle picking for subtomogram averaging, and generating many-feature
segmentations of cellular
architecture based on in situ tomography data. Featuring comprehensive annotation, segmentation,
and rendering functionality, as well as an open repository for trained models at aiscryoet. org, we
hope that Ais will help accelerate research and dissemination of data involving cryoET.

== Keywords ==

== Links ==

https://elifesciences.org/articles/98552

== Related software ==

== Related methods ==

== Comments ==