Automated cell nucleus segmentation and acute leukemia detection in blood microscopic images

Author(s):  
Subrajeet Mohapatra ◽  
Dipti Patra
1998 ◽  
Vol 71 (2) ◽  
pp. 203-213 ◽  
Author(s):  
Pascal Bamford ◽  
Brian Lovell

Author(s):  
N.H.Abd Halim ◽  
M.Y. Mashor ◽  
A.S. Abdul Nasir ◽  
N.R. Mokhtar ◽  
H. Rosline

2020 ◽  
Author(s):  
Edward M. Kong ◽  
Chenfei Hu ◽  
Byoung Soo Kim ◽  
Gabriel Popescu

AbstractThe nucleus is the largest organelle in cells carrying genetic materials that support genetic replication and transcription. It is likely that such genetic activities can influence the nuclear dry mass, but there is a lack of analytical tools enabling us to monitor dynamic changes in this quantity. To this end, this study demonstrates an image analysis script that allows us to quantify these changes in the nuclear dry mass. The script runs the cell-nuclei segmentation using Matlab. By using the fluorescent image as a template for the boundaries of cell nuclei and quantitative phase images for retrieving the dry mass density, the script recognizes nuclei of all cells in an image at a time and quantifies the nuclear dry mass. Using the “the cell-nucleus segmentation” script, this study reveals an interesting correlation between the nuclear dry mass and the filopodia protrusion of cervical epithelial cells. As the filopodia density and protrusion length increase, the nuclear dry mass increases. On the other hand, whenever the nuclear dry mass decreases, cells filopodia retract significantly. Taken together, the imaging script developed here will be useful to quantifying dynamic nuclear activities of a broad array of cells non-invasively.


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