Nature

CellSAM: a foundation model for cell segmentation

Cells are a fundamental unit of biological organization, and identifying them in imaging data—cell segmentation—is a critical task for various cellular imaging experiments. Although deep learning ...
Nature

Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge

Colorectal cancer (CRC) is the third leading cause of cancer deaths, with a reported mortality rate of nearly 51% 1. CRC can be characterised by early cancer precursors such as adenomas or serrated ...
Fred Hutch

New cell segmentation methods for better spatial transcriptomics

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 ...
Medical Xpress

Comprehensive AI model outperforms traditional methods in biomedical image segmentation

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 ...
Medical Xpress

Semi-supervised segmentation method developed for 3D medical image accuracy

A research team led by Prof. Wang Huanqin at the Institute of Intelligent Machines, the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, recently proposed a semi-supervised ...
News Medical

Deep learning method enhances vessel and plaque segmentation in stroke diagnosis

Stroke is the second leading cause of death globally. Ischemic stroke, strongly linked to atherosclerotic plaques, requires accurate plaque and vessel wall segmentation and quantification for ...