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Introducing Biomedisa as an open-source online platform for biomedical image segmentation

Lösel, Philipp D. ; Kamp, Thomas van de ; Jayme, Alejandra ; Ershov, Alexey ; Faragó, Tomáš ; Pichler, Olaf ; Tan Jerome, Nicholas ; Aadepu, Narendar ; Bremer, Sabine ; Chilingaryan, Suren A. ; Heethoff, Michael ; Kopmann, Andreas ; Odar, Janes ; Schmelzle, Sebastian ; Zuber, Marcus ; Wittbrodt, Joachim ; Baumbach, Tilo ; Heuveline, Vincent (2020)
Introducing Biomedisa as an open-source online platform for biomedical image segmentation.
In: Nature Communications, 11 (1)
doi: 10.1038/s41467-020-19303-w
Artikel, Bibliographie

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Kurzbeschreibung (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.

Typ des Eintrags: Artikel
Erschienen: 2020
Autor(en): Lösel, Philipp D. ; Kamp, Thomas van de ; Jayme, Alejandra ; Ershov, Alexey ; Faragó, Tomáš ; Pichler, Olaf ; Tan Jerome, Nicholas ; Aadepu, Narendar ; Bremer, Sabine ; Chilingaryan, Suren A. ; Heethoff, Michael ; Kopmann, Andreas ; Odar, Janes ; Schmelzle, Sebastian ; Zuber, Marcus ; Wittbrodt, Joachim ; Baumbach, Tilo ; Heuveline, Vincent
Art des Eintrags: Bibliographie
Titel: Introducing Biomedisa as an open-source online platform for biomedical image segmentation
Sprache: Englisch
Publikationsjahr: 4 November 2020
Ort: London
Verlag: Springer Nature
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Nature Communications
Jahrgang/Volume einer Zeitschrift: 11
(Heft-)Nummer: 1
Kollation: 14 Seiten
DOI: 10.1038/s41467-020-19303-w
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Kurzbeschreibung (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.

Freie Schlagworte: Imaging, Software
ID-Nummer: Artikel-ID: 5577
Sachgruppe der Dewey Dezimalklassifikatin (DDC): 500 Naturwissenschaften und Mathematik > 570 Biowissenschaften, Biologie
Fachbereich(e)/-gebiet(e): 10 Fachbereich Biologie
10 Fachbereich Biologie > Ecological Networks
Hinterlegungsdatum: 26 Sep 2024 07:32
Letzte Änderung: 26 Sep 2024 07:32
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