Fast random walker for neutrophil cell segmentation in 3D

The random walker method [1] has many nice characteristics for 3D image segmentation. However, it is computational expensive and slow due to a massive linear system to be solved. In this work, we take advantage of the probabilistic output from the random walker method applied to a small downsampled...

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Bibliographic Details
Main Authors: Cheng-Jin Du, Ferguson, J. G., Hawkins, P. T., Stephens, L. R., Bretschneider, T.
Format: Conference Proceeding
Language:English
Subjects:
3D cell segmentation
cell motility
edge-preserved upsampling
Equations
Image edge detection
Image segmentation
Level set
Microscopy
neutrophil cell segmentation
Noise measurement
Random walker
Robustness
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Summary:The random walker method [1] has many nice characteristics for 3D image segmentation. However, it is computational expensive and slow due to a massive linear system to be solved. In this work, we take advantage of the probabilistic output from the random walker method applied to a small downsampled image. By using the original image and seeds information, a novel edge-preserving method is introduced to upsample the probability, which is used for final segmentation. The running time is significantly reduced, taking less than one second to segment a 180×283×12 image stack on a normal laptop. Furthermore, the proposed method performs better when dealing with noisy boundaries than the original random walker method and the level set method.
ISSN:1945-7928
1945-8452
DOI:10.1109/ISBI.2012.6235516