Hidden Markov Measure Field Models for Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture based mammogram classification and segmentation
IWDM'06 Proceedings of the 8th international conference on Digital Mammography
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Breast dynamic contrast enhanced MRI (DCE-MRI) segmentation, based on the differential enhancement of image intensities, can help the clinician detect suspicious regions. Motivated by the recent success of texture learning and segmentation, we propose a novel segmentation method based on texture properties. The segmentation method consists of generating a library of texture primitives "textons", and then classifying each voxel into different tissue classes using textons and vector attributes. A Markov Random Measure field (MRF) method is combined with texture information to realise the spatial coherence. To evaluate our framework, twenty patients' MRIs from our local hospital were used for texture learning, and a further twenty patients' MRIs were used for testing.