Compound image segmentation of published biomedical figures.

ABSTRACT:

Motivation

Images convey essential information in biomedical publications. As such, there is a growing interest within the bio-curation and the bio-databases communities, to store images within publications as evidence for biomedical processes and for experimental results. However, many of the images in biomedical publications are compound images consisting of multiple panels, where each individual panel potentially conveys a different type of information. Segmenting such images into constituent panels is an essential first step toward utilizing images.

Results

In this article, we develop a new compound image segmentation system, FigSplit, which is based on Connected Component Analysis. To overcome shortcomings typically manifested by existing methods, we develop a quality a

SUBMITTER: Li P 

PROVIDER: S-EPMC6030860 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature