scholarly journals A thresholding method for automatic cell image segmentation.

1979 ◽  
Vol 27 (1) ◽  
pp. 180-187 ◽  
Author(s):  
H Borst ◽  
W Abmayr ◽  
P Gais

An algorithm for automatic segmentation of PAP-stained cell images and its digital implementation is described. First, the image is filtered in order to eliminate the granularily and small objects in the image which may upset the segmentation procedure. In a second step, information on gradient and compactness is extracted from the filtered image and stored in three histograms as functions of the extinction. From these histograms, two extinction thresholds are computed. These thresholds are suitable to separate the nucleus from the cytoplasm, and the cytoplasm from the background in the filtered image. Masks are determined in this way, and finally used to analyse the nucleus and the cytoplasm in the original image.

2012 ◽  
Vol 429 ◽  
pp. 298-302
Author(s):  
Zhi Gang Chen ◽  
Ai Hua Chen ◽  
Yue Li Cui

In order to more precisely segment complex microscopic cell image, a new image segmentation method by combination of coarse segmentation and fine segmentation is proposed. Firstly, the coutourlet transform and morphology are used to segment original image coarsely and get the subimages that include the particles. Then ,the Level Set method is employed to locate edge of the particles precisely. The method provides more accurate data for complex microscopic cell automatic recognition system. Taking example for complex urinary sediment image, the experiment results show that the method can segment urinary sediment images effectively and precisely and increasing the performance of urinary sediment particles recognition.


Author(s):  
Sixian Chan ◽  
Cheng Huang ◽  
Cong Bai ◽  
Weilong Ding ◽  
Shengyong Chen

2000 ◽  
Vol 33 (5) ◽  
pp. 821-832 ◽  
Author(s):  
A. Garrido ◽  
N. Pérez de la Blanca

NeuroImage ◽  
2016 ◽  
Vol 125 ◽  
pp. 479-497 ◽  
Author(s):  
Eelke Visser ◽  
Max C. Keuken ◽  
Gwenaëlle Douaud ◽  
Veronique Gaura ◽  
Anne-Catherine Bachoud-Levi ◽  
...  

2013 ◽  
Vol 734-737 ◽  
pp. 2912-2916
Author(s):  
Hui Li ◽  
Ping He

Automation strain measurement of the sheet metal deforming becomes one of the important application fields of computer vision. The algorithm of image segmentation based on adaptability threshold was presented for image segmentation of metal steel. In order to validate the proposed method, it is tested and compared with Ostu method and the one-dimensional maximum entropy method. Experiment results indicate that the method is simple and effective, and has an advantage of reservation of the main features of the original image.


2014 ◽  
Author(s):  
Ismahan Baghli ◽  
Amir Nakib ◽  
Elie Sellam ◽  
Mourtada Benazzouz ◽  
Amine Chikh ◽  
...  

Author(s):  
Geovani L. Martins ◽  
Daniel S. Ferreira ◽  
Fátima N. S. Medeiros ◽  
Geraldo L. B. Ramalho

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