An MRF model for biomedical image segmentation
D You, S Antani, D Demner-Fushman… - 2014 IEEE 27th …, 2014 - ieeexplore.ieee.org
D You, S Antani, D Demner-Fushman, GR Thoma
2014 IEEE 27th International Symposium on Computer-Based Medical …, 2014•ieeexplore.ieee.orgWe propose a Markov random field (MRF)-based method to segment photographic
biomedical images into three image sub-regions, viz., tissue, photo, and background.
Segmentation results are then used to extract local and global visual features to separate
images with tissue, such as endoscopic images, from general photographs.
biomedical images into three image sub-regions, viz., tissue, photo, and background.
Segmentation results are then used to extract local and global visual features to separate
images with tissue, such as endoscopic images, from general photographs.
We propose a Markov random field (MRF)-based method to segment photographic biomedical images into three image sub-regions, viz., tissue, photo, and background. Segmentation results are then used to extract local and global visual features to separate images with tissue, such as endoscopic images, from general photographs.
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