Segmentation of complementary DNA microarray images by wavelet-based Markov random field model.
A wavelet-based modification of the Markov random field (WMRF) model is proposed for segmenting complementary DNA (cDNA) microarray images. For evaluation purposes, five simulated and a set of five real microarray images were used. The one-level stationary wavelet transform (SWT) of each microarray image was used to form two images, a denoised image, using hard thresholding filter, and a magnitude image, from the amplitudes of the horizontal and vertical components of SWT. Elements from these two images were suitably combined to form the WMRF model for segmenting spots from their background. The WMRF was compared against the conventional MRF and the Fuzzy C means (FCM) algorithms on simulated and real microarray images and their performances were evaluated by means of the segmentation matching factor (SMF) and the coefficient of determination (r2). Additionally, the WMRF was compared against the SPOT and SCANALYZE, and performances were evaluated by the mean absolute error (MAE) and the coefficient of variation (CV). The WMRF performed more accurately than the MRF and FCM (SMF: 92.66, 92.15, and 89.22, r2 : 0.92, 0.90, and 0.84, respectively) and achieved higher reproducibility than the MRF, SPOT, and SCANALYZE (MAE: 497, 1215, 1180, and 503, CV: 0.88, 1.15, 0.93, and 0.90, respectively).
Medical Image Processing and Analysis Group, Laboratory of Medical Physics, School of Medical Science, University of Patras, 26 500 Rio Patras, Greece. mathan@upatras.gr
Emmanouil I
EI
Athanasiadis
Dionisis A
DA
Cavouras
Dimitris Th
DT
Glotsos
Pantelis V
PV
Georgiadis
Ioannis K
IK
Kalatzis
George C
GC
Nikiforidis
D000465:Algorithms; D016000:Cluster Analysis; D003198:Computer Simulation; D017143:Fuzzy Logic; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008390:Markov Chains; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D015203:Reproducibility of Results