The AI-Powered Pixel Classifier
Fast and reproducible microscopy-image segmentation results
Quantitative analysis of a sample’s microstructure is based on image segmentation, but dividing the image into constituent objects of interest and their local background is a challenge for scientists. Classical function-based automation has its limits for classifying images. Achieving reproducible results manually requires expertise and is tedious work. But now there is a way to overcome these challenges by speeding up this analysis to extract the real value of the image and gain insights. The artificial-intelligence-powered pixel classifier provides reproducible segmentation results fast and overcomes human action. It delivers more robust results compared to classical function-based automation. And here is why …
Related Articles
-
Spatial Analysis of Neuroimmune Interactions in Alzheimer’s Disease
Alzheimer’s disease (AD) is a complex neurodegenerative disorder characterized by neurofibrillary…
Nov 11, 2024Read article -
A Guide to Spatial Biology
What is spatial biology, and how can researchers leverage its tools to meet the growing demands of…
Oct 10, 2024Read article -
Probing Human Alzheimer's Cortical Section using Spatial Multiplexing
Alzheimer’s disease (AD) is the most common neurodegenerative disease and is characterized by the…
Sep 17, 2024Read article
