Name
Abstract | ||
|---|---|---|
•Karyotyping is a popular method of chromosome analysis in cytogenetic laboratories to diagnose the genetic disorders.•Finding analyzable metaphase images is essential for karyotyping that needs to be done automatically and accurately.•Automation of finding analyzable metaphase images reduces the interobservor variation and speeds-up the karyotyping.•Enhancing the sensitivity and specificity of this task, has big effect on overal accuracy of karyotyping resulting to the more accurate diagnosis.•An automated high accurate metaphase finder decreases the clinical and sampling work and costs. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.bspc.2019.04.017 | Biomedical Signal Processing and Control |
Keywords | Field | DocType |
Metaphase detection,Karyotyping,Deep convolutional neural networks | Metaphase,False positive rate,Computer vision,Pattern recognition,Convolutional neural network,Image processing,Feature extraction,Artificial intelligence,Component analysis,Artificial neural network,True positive rate,Mathematics | Journal |
Volume | ISSN | Citations |
52 | 1746-8094 | 1 |
PageRank | References | Authors |
0.36 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yaser Moazzen | 1 | 4 | 1.77 |
| Abdulkerim Çapar | 2 | 19 | 4.28 |
| Abdulkadir Albayrak | 3 | 6 | 2.86 |
| Calik, Nurullah | 4 | 2 | 2.42 |
| Behçet Uğur Töreyin | 5 | 1 | 0.36 |