Classification of breast tissue by texture analysis
Image and Vision Computing - Special issue: BMVC 1991
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Spatiograms versus Histograms for Region-Based Tracking
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Mammographic Segmentation Based on Texture Modelling of Tabár Mammographic Building Blocks
IWDM '08 Proceedings of the 9th international workshop on Digital Mammography
A Statistical Approach to Material Classification Using Image Patch Exemplars
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automated assessment of breast tissue density in digital mammograms
Computer Vision and Image Understanding
Object detection using spatial histogram features
Image and Vision Computing
IWDM'06 Proceedings of the 8th international conference on Digital Mammography
Breast density segmentation using texture
IWDM'06 Proceedings of the 8th international conference on Digital Mammography
Image analysis with local binary patterns
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
A Novel Breast Tissue Density Classification Methodology
IEEE Transactions on Information Technology in Biomedicine
Intensity independent texture analysis in screening mammograms
IWDM'12 Proceedings of the 11th international conference on Breast Imaging
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We have developed a segmentation approach, which is based on modelling local texture information and incorporates both greylevel and spatial aspects Variation in local greylevel configuration/appearance is represented in histogram format for which the distribution varies with texture appearance Segmentation results based on full mammographic images are presented In addition, the potential use of the segmentation results for mammographic risk assessment and abnormality detection is discussed.