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Integrated local binary pattern texture features for classification of breast tissue imaged by optical coherence microscopy
2017
Medical Image Analysis
This paper proposes a texture analysis technique that can effectively classify different types of human breast tissue imaged by Optical Coherence Microscopy (OCM). OCM is an emerging imaging modality for rapid tissue screening and has the potential to provide high resolution microscopic images that approach those of histology. OCM images, acquired without tissue staining, however, pose unique challenges to image analysis and pattern classification. We examined multiple types of texture features
doi:10.1016/j.media.2017.03.002
pmid:28327449
pmcid:PMC5479412
fatcat:3ojvs5n3kvhfbfclgmagph2i6u