Name
Title | ||
|---|---|---|
The Image-Based Analysis And Classification Of Urine Sediments Using A Lenet-5 Neural Network |
Abstract | ||
|---|---|---|
In this work, we presented a deep learning approach based on the LeNet-5 network for analysing and classifying recognisable shapes in urine sample images. The approach is based on shape analysis to recognise and classify red blood cells, white blood cells, epithelial cells and crystals observed under microscopes in urine samples. We modified the LeNet-5 neural network by changing the numbers of output nodes and convolutional layers. We compared the results of our method with those obtained by traditional feature extraction followed by back-propagation neural networks. Our testing showed that our method achieved a higher accuracy, sensitivity and specificity. The performance of our method demonstrated its broad applicability in urine sample analysis. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1080/21681163.2019.1608307 | COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION |
Keywords | Field | DocType |
LeNet-5 network, back-propagation neutral networks, urine sample analysis | Pattern recognition,Computer science,Image based,Artificial intelligence,Deep learning,Artificial neural network | Journal |
Volume | Issue | ISSN |
8 | 1 | 2168-1163 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
12 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Taihao Li | 1 | 0 | 0.68 |
| Taihao Li | 2 | 0 | 0.68 |
| Di Jin | 3 | 9 | 3.15 |
| Cuifen Du | 4 | 0 | 0.34 |
| Xiumei Cao | 5 | 0 | 0.34 |
| Haige Chen | 6 | 0 | 0.34 |
| Jianshe Yan | 7 | 0 | 0.68 |
| Jianshe Yan | 8 | 0 | 0.68 |
| Na Chen | 9 | 1 | 1.64 |
| Zhenyi Chen | 10 | 0 | 1.01 |
| Zhenzhen Feng | 11 | 0 | 0.34 |
| Shupeng Liu | 12 | 2 | 1.71 |