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Summary: Hybrid Spot Segmentation in Four-Channel
Microarray Genotyping Image Data
Mohsen Abbaspoura, Rafeef Abugharbieha, Mohua Podderb,c, Ben W. Tripp c, and Scott J. Tebbuttc
a
Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada, V6T 1Z4
b
Department of Statistics, University of British Columbia, Vancouver, Canada, V6T 1Z2
c
iCAPTURE Centre (Department of Medicine), St. Paul's Hospital, University of British Columbia, Vancouver, Canada V6Z 1Y6
rafeef@ece.ubc.ca
Abstract-- In this paper we present a novel hybrid algorithm
for spot segmentation in four-channel genotyping microarray
images. A new four-dimensional clustering approach for fully-
automated spot segmentation is proposed, along with a new
iterative method to automatically identify the number of clusters
in a single-spot area. A spatial shape detection step is simul-
taneously applied, which assists a nonlinear diffusion filtering
step in detecting the connected objects, while a spot masking
step prevents various noise types from misleading the spot
extraction algorithm. The developed analysis system successfully
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