Cell segmentation is a crucial step in numerous biomedical imaging endeavors—so much so that the community is flooded with publicly available, state-of-the-art segmentation techniques ready for out-of ...

This important work presents a self-supervised method for the segmentation of 3D cells in fluorescent microscopy images, conveniently packaged as a Napari plugin and tested on an annotated dataset.

An app for segmentation and classification of images of cells from optical microscope. This project uses marker controlled watershed (openCv), and pretrained ResNet-50 model (tensorflow) a ...

An app for segmentation and classification of images of cells from optical microscope. This project uses marker controlled watershed (openCv), and pretrained ResNet-50 model (tensorflow) ...

Identifying and delineating cell structures in microscopy images is crucial for understanding the complex processes of life. This task is called "segmentation" and it enables a range of applications, ...

Abstract: Cell segmentation is a key step in medical image analysis and cell biology research, and is important in areas such as understanding cell behaviour, cancer detection and cell cycle analysis.

PLEASANTON, Calif., Feb. 23, 2025 /PRNewswire/ -- At the Advances in Genome Biology and Technology (AGBT) General Meeting, 10x Genomics, Inc. (Nasdaq: TXG), a leader in single cell and spatial biology ...