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Analysis of Mammographic Microcalcification Clusters Using Topological Features.

, , , and . Digital Mammography / IWDM, volume 8539 of Lecture Notes in Computer Science, page 620-627. Springer, (2014)

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Analysis of Mammographic Microcalcification Clusters Using Topological Features., , , and . Digital Mammography / IWDM, volume 8539 of Lecture Notes in Computer Science, page 620-627. Springer, (2014)Meningioma subtype classification using morphology features and random forests., and . Medical Imaging: Digital Pathology, volume 8676 of SPIE Proceedings, page 86760S. SPIE, (2013)Parallel Projections for Manifold Learning., and . ICMLA, page 266-271. IEEE Computer Society, (2010)Non-expert Classification of Microcalcification Clusters Using Mereotopological Barcodes., and . Digital Mammography / IWDM, volume 9699 of Lecture Notes in Computer Science, page 351-358. Springer, (2016)Piecewise-linear manifold learning: A heuristic approach to non-linear dimensionality reduction., and . Intell. Data Anal., 19 (6): 1213-1232 (2015)Piecewise-linear manifold learning.. Aberystwyth University, UK, (2011)British Library, EThOS.Texture segmentation using different orientations of GLCM features., , and . MIRAGE, page 17:1-17:8. ACM, (2013)Topological Modeling and Classification of Mammographic Microcalcification Clusters., , , , , and . IEEE Trans. Biomed. Eng., 62 (4): 1203-1214 (2015)Myofibre segmentation in H&E stained adult skeletal muscle images using coherence-enhancing diffusion filtering., , and . BMC Medical Imaging, (2014)Modelling mammographic microcalcification clusters using persistent mereotopology., , , and . Pattern Recognit. Lett., (2014)