Conditional Random Fields for image segmentation in Intravascular Ultrasound
نویسندگان
چکیده
We present a Conditional Random Fields based approach for segmenting Intravascular Ultrasound (IVUS) images. The presented method uses a contextual discriminative graphical model to deal with the presence of distortions and artifacts in IVUS images, that turns the segmentation of interesting regions into a difficult task. An accurate lumen segmentation on IVUS longitudinal images is achieved.
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