EM-stellar: benchmarking deep learning for electron microscopy image segmentation.

ABSTRACT:

Motivation

The inherent low contrast of electron microscopy (EM) datasets presents a significant challenge for rapid segmentation of cellular ultrastructures from EM data. This challenge is particularly prominent when working with high-resolution big-datasets that are now acquired using electron tomography and serial block-face imaging techniques. Deep learning (DL) methods offer an exciting opportunity to automate the segmentation process by learning from manual annotations of a small sample of EM data. While many DL methods are being rapidly adopted to segment EM data no benchmark analysis has been conducted on these methods to date.

Results

We present EM-stellar, a platform that is hosted on Google Colab that can be used to benchmark the performance of a range of state-of

SUBMITTER: Khadangi A 

PROVIDER: S-EPMC8034537 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature