An Instance Segmentation Dataset of Yeast Cells in Microstructures.
Annu Int Conf IEEE Eng Med Biol Soc
; 2023: 1-4, 2023 07.
Article
en En
| MEDLINE
| ID: mdl-38083295
Extracting single-cell information from microscopy data requires accurate instance-wise segmentations. Obtaining pixel-wise segmentations from microscopy imagery remains a challenging task, especially with the added complexity of microstructured environments. This paper presents a novel dataset for segmenting yeast cells in microstructures. We offer pixel-wise instance segmentation labels for both cells and trap microstructures. In total, we release 493 densely annotated microscopy images. To facilitate a unified comparison between novel segmentation algorithms, we propose a standardized evaluation strategy for our dataset. The aim of the dataset and evaluation strategy is to facilitate the development of new cell segmentation approaches. The dataset is publicly available at https://christophreich1996.github.io/yeast_in_microstructures_dataset/.
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1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Saccharomyces cerevisiae
/
Procesamiento de Imagen Asistido por Computador
Idioma:
En
Revista:
Annu Int Conf IEEE Eng Med Biol Soc
Año:
2023
Tipo del documento:
Article
Pais de publicación:
Estados Unidos