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Segmentation of light and dark hair in dermoscopic images: a hybrid approach using a universal kernel.

, , и . Medical Imaging: Image Processing, том 7623 из SPIE Proceedings, стр. 76234N. SPIE, (2010)

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Global pattern analysis and classification of dermoscopic images using textons., , , , и . Medical Imaging: Image Processing, том 8314 из SPIE Proceedings, стр. 83144X. SPIE, (2012)Tree Structured Model of Skin Lesion Growth Pattern via Color Based Cluster Analysis., , и . MLMI, том 7009 из Lecture Notes in Computer Science, стр. 291-299. Springer, (2011)Detection and Analysis of Irregular Streaks in Dermoscopic Images of Skin Lesions., , , , и . IEEE Trans. Med. Imaging, 32 (5): 849-861 (2013)Determining the Asymmetries of Skin Lesions with Fuzzy Borders., , и . BIBE, стр. 223-230. IEEE Computer Society, (2003)Generalizing Common Tasks in Automated Skin Lesion Diagnosis., , , , и . IEEE Trans. Information Technology in Biomedicine, 15 (4): 622-629 (2011)Segmentation of light and dark hair in dermoscopic images: a hybrid approach using a universal kernel., , и . Medical Imaging: Image Processing, том 7623 из SPIE Proceedings, стр. 76234N. SPIE, (2010)Automatic detection and segmentation of vascular structures in dermoscopy images using a novel vesselness measure based on pixel redness and tubularness., , , и . Medical Imaging: Computer-Aided Diagnosis, том 9414 из SPIE Proceedings, стр. 94143M. SPIE, (2015)A Fully Automatic Random Walker Segmentation for Skin Lesions in a Supervised Setting., , , и . MICCAI (1), том 5762 из Lecture Notes in Computer Science, стр. 1108-1115. Springer, (2009)Automatic detection of translucency using a deep learning method from patches of clinical basal cell carcinoma images., , , , , и . APSIPA, стр. 685-688. IEEE, (2018)Computer-aided detection of basal cell carcinoma through blood content analysis in dermoscopy images., , , , и . Medical Imaging: Computer-Aided Diagnosis, том 10575 из SPIE Proceedings, стр. 105750O. SPIE, (2018)