Texture Information in Melanocytic Skin Lesion Analysis Based on Standard Camera Images
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[1] C. H. Chen,et al. Handbook of Pattern Recognition and Computer Vision , 1993 .
[2] Fred Godtliebsen,et al. Automatic learning of spatial patterns for diagnosis of skin lesions , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.
[3] Michael Binder,et al. Limitations of dermoscopy in the recognition of melanoma. , 2005, Archives of dermatology.
[4] S. T. Buckland,et al. An Introduction to the Bootstrap. , 1994 .
[5] W. Stolz,et al. Can early malignant melanoma be differentiated from atypical melanocytic nevi by in vivo techniques? , 1997, Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging.
[6] Hsien-Che Lee,et al. Introduction to Color Imaging Science , 2005 .
[7] Rainer Hofmann-Wellenhof,et al. Teledermatology: an update. , 2008, Seminars in cutaneous medicine and surgery.
[8] David A Clausi. An analysis of co-occurrence texture statistics as a function of grey level quantization , 2002 .
[9] Prasanta Sahoo,et al. Fractal Analysis in Machining (SpringerBriefs in Applied Sciences and Technology / SpringerBriefs in Computational Mechanics) , 2011 .
[10] Gerard de Haan,et al. Automatic imaging sysem with decision support for inspection of pigmented skin lesions and melanoma diagnosis. , 2009 .
[11] E. Oja,et al. Independent Component Analysis , 2013 .
[12] Jacob Scharcanski,et al. Shading Attenuation in Human Skin Color Images , 2010, ISVC.
[13] K Wolff,et al. In vivo epiluminescence microscopy of pigmented skin lesions. I. Pattern analysis of pigmented skin lesions. , 1987, Journal of the American Academy of Dermatology.
[14] S. Zucker,et al. Evaluating the fractal dimension of profiles. , 1989, Physical review. A, General physics.
[15] C. Allain,et al. Characterizing the lacunarity of random and deterministic fractal sets. , 1991, Physical review. A, Atomic, molecular, and optical physics.
[16] Matti Pietikäinen,et al. A comparative study of texture measures with classification based on featured distributions , 1996, Pattern Recognit..
[17] Evgenia I. Tsompanaki,et al. A simple digital image processing system to aid in melanoma diagnosis in an everyday melanocytic skin lesion unit. A preliminary report , 2006, International journal of dermatology.
[18] Maria Petrou,et al. Image Processing: The Fundamentals: Petrou/Image Processing: The Fundamentals , 2010 .
[19] Hsien-Che Lee. Introduction to Color Imaging Science: Index , 2005 .
[20] Jacob Scharcanski,et al. An ICA-based method for the segmentation of pigmented skin lesions in macroscopic images , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[21] R. Johr. Dermoscopy: alternative melanocytic algorithms-the ABCD rule of dermatoscopy, Menzies scoring method, and 7-point checklist. , 2002, Clinics in dermatology.
[22] Marek Elbaum,et al. Can early malignant melanoma be differentiated from atypical melanocytic nevus by in vivo techniques? , 1997, Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging.
[23] Prasanta Sahoo,et al. Fractal Analysis in Machining , 2011 .
[24] Riccardo Bono,et al. Melanoma Computer-Aided Diagnosis , 2004, Clinical Cancer Research.
[25] E. Warshaw,et al. Dermatoscopy use by US dermatologists: a cross-sectional survey. , 2010, Journal of the American Academy of Dermatology.
[26] Masafumi Hagiwara,et al. An improved Internet-based melanoma screening system with dermatologist-like tumor area extraction algorithm , 2008, Comput. Medical Imaging Graph..
[27] Jacob Scharcanski,et al. Automated prescreening of pigmented skin lesions using standard cameras , 2011, Comput. Medical Imaging Graph..
[28] Leen-Kiat Soh,et al. Texture analysis of SAR sea ice imagery using gray level co-occurrence matrices , 1999, IEEE Trans. Geosci. Remote. Sens..
[29] Matti Pietikäinen,et al. Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns , 2002, IEEE Trans. Pattern Anal. Mach. Intell..
[30] Robert M. Haralick,et al. Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..
[31] N. Otsu. A threshold selection method from gray level histograms , 1979 .
[32] Anil K. Jain,et al. Texture Analysis , 2018, Handbook of Image Processing and Computer Vision.
[33] J. Glimm,et al. Detection of cancer-specific markers amid massive mass spectral data , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[34] Lucila Ohno-Machado,et al. A Comparison of Machine Learning Methods for the Diagnosis of Pigmented Skin Lesions , 2001, J. Biomed. Informatics.
[35] Ethem Alpaydin,et al. Introduction to Machine Learning (Adaptive Computation and Machine Learning) , 2004 .
[36] Ali Esteki,et al. Extraction of skin lesion texture features based on independent component analysis , 2009, Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging.
[37] Tony F. Chan,et al. Active Contours without Edges for Vector-Valued Images , 2000, J. Vis. Commun. Image Represent..
[38] Jacob Scharcanski,et al. Macroscopic Pigmented Skin Lesion Segmentation and Its Influence on Lesion Classification and Diagnosis , 2013 .
[39] Maria Petrou,et al. Image processing - the fundamentals , 1999 .
[40] T Fikrle,et al. Digital computer analysis of dermatoscopical images of 260 melanocytic skin lesions; perimeter/area ratio for the differentiation between malignant melanomas and melanocytic nevi , 2007, Journal of the European Academy of Dermatology and Venereology : JEADV.
[41] Aapo Hyvärinen,et al. Fast and robust fixed-point algorithms for independent component analysis , 1999, IEEE Trans. Neural Networks.
[42] Aapo Hyv. Fast and Robust Fixed-Point Algorithms for Independent Component Analysis , 1999 .
[43] Aglaia G. Manousaki,et al. Use of color texture in determining the nature of melanocytic skin lesions - a qualitative and quantitative approach , 2006, Comput. Biol. Medicine.
[44] Randy H. Moss,et al. A methodological approach to the classification of dermoscopy images , 2007, Comput. Medical Imaging Graph..
[45] W. Stolz,et al. The ABCD rule of dermatoscopy. High prospective value in the diagnosis of doubtful melanocytic skin lesions. , 1994, Journal of the American Academy of Dermatology.
[46] Benoit B. Mandelbrot,et al. Fractal Geometry of Nature , 1984 .