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 (2024)
Introducing Biomedisa as an open-source online platform for biomedical image segmentation.
In: Nature Communications, 2020, 11 (1)
doi: 10.26083/tuprints-00023978
Artikel, Zweitveröffentlichung, Verlagsversion
 | Es ist eine neuere Version dieses Eintrags verfügbar. |
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: | 2024 |
| 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: | Zweitveröffentlichung |
| Titel: | Introducing Biomedisa as an open-source online platform for biomedical image segmentation |
| Sprache: | Englisch |
| Publikationsjahr: | 25 September 2024 |
| Ort: | Darmstadt |
| Publikationsdatum der Erstveröffentlichung: | 4 November 2020 |
| Ort der Erstveröffentlichung: | London |
| Verlag: | Springer Nature |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Nature Communications |
| Jahrgang/Volume einer Zeitschrift: | 11 |
| (Heft-)Nummer: | 1 |
| Kollation: | 14 Seiten |
| DOI: | 10.26083/tuprints-00023978 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/23978 |
| Zugehörige Links: | |
| Herkunft: | Zweitveröffentlichung DeepGreen |
| 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 |
| Status: | Verlagsversion |
| URN: | urn:nbn:de:tuda-tuprints-239785 |
| 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: | 25 Sep 2024 11:47 |
| Letzte Änderung: | 26 Sep 2024 07:31 |
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| Suche nach Titel in: | TUfind oder in Google |
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- Introducing Biomedisa as an open-source online platform for biomedical image segmentation. (deposited 25 Sep 2024 11:47) [Gegenwärtig angezeigt]
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