Segmentation of touching cell nuclei using gradient flow tracking.
Reliable cell nuclei segmentation is an important yet unresolved problem in biological imaging studies. This paper presents a novel computerized method for robust cell nuclei segmentation based on gradient flow tracking. This method is composed of three key steps: (1) generate a diffused gradient vector flow field; (2) perform a gradient flow tracking procedure to attract points to the basin of a sink; and (3) separate the image into small regions, each containing one nucleus and nearby peripheral background, and perform local adaptive thresholding in each small region to extract the cell nucleus from the background. To show the generality of the proposed method, we report the validation and experimental results using microscopic image data sets from three research labs, with both over-segmentation and under-segmentation rates below 3%. In particular, this method is able to segment closely juxtaposed or clustered cell nuclei, with high sensitivity and specificity in different situations.
Li
G
G
School of Automation, Northwestern Polytechnic University, Xi'an, China.
Liu
T
T
Nie
J
J
Guo
L
L
Chen
J
J
Zhu
J
J
Xia
W
W
Mara
A
A
Holley
S
S
Wong
S T C
ST
D000818:Animals; D002451:Cell Compartmentation; D002467:Cell Nucleus / Q000502:physiology* / Q000648:ultrastructure*; D004058:Diffusion; D007091:Image Processing, Computer-Assisted; D008853:Microscopy / Q000379:methods*; D008954:Models, Biological; D015027:Zebrafish