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About Erik Lamoureux - Red Blood Cell Deformability Image Classification Using Deep Learning
This document summarizes research using a convolutional neural network (CNN) to classify red blood cell deformability levels based on microscope images. The researchers developed a CNN model to determine deformability and compared it to classifications from a microfluidic cell sorting device. For a sample from a single fresh donor, the CNN achieved 86% accuracy on test images at classifying deformability levels determined by the microfluidic sorter, demonstrating the CNN approach can determine deformability levels comparable to microfluidic sorting. The goal is to apply this CNN approach to multiple donor samples to identify long-lasting transfusion blood.
Detailed Information
| Author: | ['CBR UBC'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 1 |
| Language: | English |
| Format: | |
| Price: | FREE |
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