Artificial Intelligence Approaches to Assessing Primary Cilia

Ruchi Bansal; Staci E. Engle; Tisianna K. Kamba; Kathryn M. Brewer; Wesley R. Lewis; Nicolas F. Berbari

doi:10.3791/62521

ジャーナル

/

生物学

/

Artificial Intelligence Approaches to Assessing Primary Cilia

JoVE Journal
生物学

This content is Free Access.

JoVE Journal 生物学

Artificial Intelligence Approaches to Assessing Primary Cilia

2,990 Views

•

08:58 min

•

May 01, 2021

DOI:

10.3791/62521-v

DOI:

10.3791/62521-v

•

08:58 min

May 01, 2021

•

9 Views

Ruchi Bansal¹, Staci E. Engle¹, Tisianna K. Kamba¹, Kathryn M. Brewer¹, Wesley R. Lewis², Nicolas F. Berbari^1,3,4

¹生物学科,Indiana University-Purdue University Indianapolis, ²Nikon Instruments Inc., ³Stark Neurosciences Research Institute,Indiana University, ⁴Center for Diabetes and Metabolic Diseases,Indiana University School of Medicine

概要

The use of artificial intelligence (Ai) to analyze images is emerging as a powerful, less biased, and rapid approach compared with commonly used methods. Here we trained Ai to recognize a cellular organelle, primary cilia, and analyze properties such as length and staining intensity in a rigorous and reproducible manner.

Explore More Videos

AI Artificial Intelligence Cilia Analysis Image Analysis Organelle Analysis Cytoskeletal Proteins ND File Image Calibration Binary Toolbar Auto Detect Draw Object NIS.AI Train Segment.AI GroundTruth Binaries Confocal Images Multi-point Wavelength Channel Selection

Read Article

Artificial Intelligence Approaches to Assessing Primary Cilia

概要

Automatically generated

Explore More Videos