Red blood cell phenotyping from 3D confocal images using artificial neural networks

Abstract excerpt

The investigation of cell shapes mostly relies on the manual classification of 2D images, causing a subjective and time consuming evaluation based on a portion of the cell surface. We present a dual-stage neural network architecture for analyzing fine shape details from confocal microscopy recordings in 3D. The system, tested on red blood cells, uses training data from both healthy donors and patients with a...

Topics

Share this publication in a Topic to start or enrich a Post.

• Share to Cell Image Analysis Techniques
• Share to Erythrocyte Function and Pathophysiology