Compare deep learning cell segmentation tools Cellpose and StarDist: how each works, how they differ by imaging type, and ...

Single-cell RNA transcriptomics allows researchers to broadly profile the gene expression of individual cells in a particular tissue. This technique has allowed researchers to identify new subsets of ...

Researchers at Children's Hospital of Philadelphia (CHOP) announced the creation of a new AI technology called CelloType, a comprehensive model designed to more accurately identify and classify cells ...

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, ...

An example of a cell image before and after segmentation, a process which allows researchers to distinguish single cells from each other and their background. Observing individual cells through ...

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, ...

Researchers have developed a method to use an image generation AI model to create realistic images of single cells, which are then used as 'synthetic data' to train an AI model to better carry out ...

In this interview, AZoLife Sciences speaks with Boyd Butler, a microscopy and high-content screening expert at Molecular ...

Artificial intelligence (AI) in research histopathology is turning whole-slide images of preclinical tissue into structured, quantitative data rather than a pathologist's subjective impression alone.