ArticleNature communications2020
Introducing Biomedisa as an open-source online platform for biomedical image segmentation.
Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 89 papers, 1 of them a synthesis that pooled it.
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Who cites it
89 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Clinical application of HEDI for biomechanical evaluation and visualisation in incisional hernia repair.Communications medicine · 2026Article
29 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We present Biomedisa, a free and easy-to-use open-source online platform developed for semi-automatic segmentation of large volumetric images. The segmentation is based on a smart interpolation of sparsely pre-segmented slices taking into account the complete underlying image data. Biomedisa is particularly valuable when little a priori knowledge is available, e.g. for the dense annotation of the training data for a deep neural network. The platform is accessible through a web browser and requires no complex and tedious configuration of software and model parameters, thus addressing the needs of scientists without substantial computational expertise. We demonstrate that Biomedisa can drastically reduce both the time and human effort required to segment large images. It achieves a significant improvement over the conventional approach of densely pre-segmented slices with subsequent morphological interpolation as well as compared to segmentation tools that also consider the underlying image data. Biomedisa can be used for different 3D imaging modalities and various biomedical applications.
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