Abstract
Combining photoacoustic (PA) imaging with laser speckle (LS) imaging (LSI)
can simultaneously determine total hemoglobin concentration (HbT), hemoglobin oxygen
saturation (SO2), and blood flow rates. Thus, the co-registration of PA and LS
images is important in physiological studies and pathological diagnosis. This letter
presents a co-registration algorithm combining mutual information with the maximum
between-class variance segmentation method (Otsu method). The mutual information and
Otsu method are used to provide the registration measure criterion and image feature
recognition, respectively. The evaluation results show that the registration
function possesses a single maximum peak and high smoothness across the global
co-registration district, indicating a robust behavior. Moreover, this method has
good registration accuracy, and the fusion result simultaneously visualizes the
separate functional information of two kinds of images.
© 2012 Chinese Optics Letters
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