Name
Abstract | ||
|---|---|---|
The application of the convolution neural network for detection of the micro nucleuses in the human lymphocyte images acquired by the image flow cytometer is considered in this paper. The existing method of detection, called IMAQ Match Pattern, is described and its limitations concerning zoom factors are analyzed. The training algorithm of the convolution neural network and the detection procedure were described. The performance of both detection methods, convolution neural network and IMAQ Match Pattern, were researched. Our results show that the convolution neural network overcomes the IMAQ Match Pattern in terms of improvement of detection rate and decreasing the numbers of false alarms. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-15819-3_68 | ICANN (1) |
Keywords | Field | DocType |
micro nucleus,convolution neural network,detection procedure,existing method,detection method,detection rate,micro nucleus detection,human lymphocyte image,false alarm,imaq match pattern,convolutional neural network,image flow cytometer,image processing,neural network | Computer vision,Image flow,False alarm,Pattern recognition,Convolutional neural network,Computer science,Zoom,Image processing,Time delay neural network,Artificial intelligence,Face detection,Machine learning | Conference |
Volume | ISSN | ISBN |
6352 | 0302-9743 | 3-642-15818-8 |
Citations | PageRank | References |
2 | 0.39 | 13 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ihor Paliy | 1 | 6 | 2.49 |
| Francesco Lamonaca | 2 | 99 | 18.81 |
| Volodymyr Turchenko | 3 | 33 | 7.57 |
| Domenico Grimaldi | 4 | 183 | 32.19 |
| Anatoly Sachenko | 5 | 30 | 8.74 |