3D-Cell-Annotator: an open-source active surface tool for single-cell segmentation in 3D microscopy images
  • Metaadatok
Tartalom: http://real.mtak.hu/120216/
Archívum: REAL
Gyűjtemény: Status = Published
Subject = Q Science / természettudomány: QH Natural history / természetrajz: QH301 Biology / biológia
Type = Article
Cím:
3D-Cell-Annotator: an open-source active surface tool for single-cell segmentation in 3D microscopy images
Létrehozó:
Tasnádi, Ervin A.
Tóth, Tímea
Kovács, Mária
Diósdi, Ákos
Pampaloni, Francesco
Molnár, József
Horváth, Péter
Kiadó:
Oxford University Press
Dátum:
2020
Téma:
QH301 Biology / biológia
Tartalmi leírás:
Segmentation of single cells in microscopy images is one of the major challenges in computational biology. It is the first step of most bioimage analysis tasks, and essential to create training sets for more advanced deep learning approaches. Here, we propose 3D-Cell-Annotator to solve this task using 3D active surfaces together with shape descriptors as prior information in a semi-automated fashion. The software uses the convenient 3D interface of the widely used Medical Imaging Interaction Toolkit (MITK). Results on 3D biological structures (e.g. spheroids, organoids, embryos) show that the precision of the segmentation reaches the level of a human expert.3D-Cell-Annotator is implemented in CUDA/C ++ as a patch for the segmentation module of MITK. The 3D-Cell-Annotator enabled MITK distribution can be downloaded at: www.3D-cell-annotator.org. It works under Windows 64-bit systems and recent Linux distributions even on a consumer level laptop with a CUDA-enabled video card using recent NVIDIA drivers.Supplementary data are available at Bioinformatics online.
Nyelv:
angol
Típus:
Article
PeerReviewed
info:eu-repo/semantics/article
Formátum:
text
Azonosító:
Tasnádi, Ervin A. and Tóth, Tímea and Kovács, Mária and Diósdi, Ákos and Pampaloni, Francesco and Molnár, József and Horváth, Péter (2020) 3D-Cell-Annotator: an open-source active surface tool for single-cell segmentation in 3D microscopy images. BIOINFORMATICS, 36 (9). pp. 2948-2949. ISSN 1367-4803
Kapcsolat:
MTMT:31138477 doi: 10.1093/bioinformatics/btaa029