Cervical Cell Classification Based Exclusively on Nucleus Features

Author(s):  
Marina E. Plissiti ◽  
Christophoros Nikou
2018 ◽  
Vol 7 (5) ◽  
pp. S66 ◽  
Author(s):  
Vanessa Martin ◽  
Tae Hun Kim ◽  
Melanie Kwon ◽  
Mohammed Kuko ◽  
Mohammad Pourhomayoun ◽  
...  

2020 ◽  
Vol 93 ◽  
pp. 106311 ◽  
Author(s):  
N. Dong ◽  
L. Zhao ◽  
C.H. Wu ◽  
J.F. Chang

2021 ◽  
Author(s):  
Jianfang Chang ◽  
Na Dong ◽  
Qingyue Feng ◽  
Xinyu Liu

2017 ◽  
Vol 21 (6) ◽  
pp. 1633-1643 ◽  
Author(s):  
Ling Zhang ◽  
Le Lu ◽  
Isabella Nogues ◽  
Ronald M. Summers ◽  
Shaoxiong Liu ◽  
...  

1977 ◽  
Vol 25 (7) ◽  
pp. 696-701 ◽  
Author(s):  
L H Oliver ◽  
R S Poulsen ◽  
G T Toussaint

The performance of a cell recognition system on unknown data is often estimated in terms of its error rates on a test set. This paper investigates methods for producing estimates of error rates in cervical cell classification. Classification performance curves calculated using these methods are given for several classification schemes used to classify 1500 cervical cells.


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