Quantitative assessment of tumour extraction from dermoscopy images and evaluation of computer-based extraction methods for an automatic melanoma diagnostic system
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Masafumi Hagiwara | Hitoshi Iyatomi | Giuseppe Argenziano | Hiroshi Oka | H. Peter Soyer | Masaru Tanaka | G. Argenziano | Masaru Tanaka | H. Iyatomi | H. Oka | K. Ogawa | H. Peter Soyer | Masataka Saito | Ayako Miyake | Masayuki Kimoto | Jun Yamagami | Seiichiro Kobayashi | Akiko Tanikawa | Koichi Ogawa | J. Yamagami | A. Tanikawa | Seiichiro Kobayashi | M. Kimoto | A. Miyake | M. Hagiwara | Masataka Saito
[1] Louis B. Rosenfeld,et al. Information architecture for the world wide web - designing large-scale web sites , 1998 .
[2] Pietro Rubegni,et al. Automated diagnosis of pigmented skin lesions , 2002, International journal of cancer.
[3] Guillod Joel,et al. Validation of segmentation techniques for digital dermoscopy , 2002, 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.
[4] H P Soyer,et al. Internet‐based program for automatic discrimination of dermoscopic images between melanomas and Clark naevi , 2004, The British journal of dermatology.
[5] R. H. Moss,et al. Neural network diagnosis of malignant melanoma from color images , 1994, IEEE Transactions on Biomedical Engineering.
[6] Gernot Rassner,et al. Primary cutaneous melanoma. Identification of prognostic groups and estimation of individual prognosis for 5093 patients , 1995, Cancer.
[7] R. B. Goudie,et al. UNSTABLE MUTATIONS IN VITILIGO , 1980, The Lancet.
[8] E. Gassner,et al. Automated melanoma recognition , 2001, IEEE Transactions on Medical Imaging.
[9] Clement T. Yu,et al. Segmentation of skin cancer images , 1999, Image Vis. Comput..
[10] C. Garbe,et al. Primary cutaneous melanoma. Optimized cutoff points of tumor thickness and importance of clark's level for prognostic classification , 1995, Cancer.
[11] William V. Stoecker,et al. Unsupervised color image segmentation: with application to skin tumor borders , 1996 .
[12] G Pellacani,et al. Digital videomicroscopy improves diagnostic accuracy for melanoma. , 1998, Journal of the American Academy of Dermatology.
[13] Josef Smolle,et al. EARLY DIAGNOSIS OF MALIGNANT MELANOMA BY SURFACE MICROSCOPY , 1987, The Lancet.
[14] P. Schmid. Segmentation of digitized dermatoscopic images by two-dimensional color clustering , 1999, IEEE Transactions on Medical Imaging.
[15] N Otsu,et al. An automatic threshold selection method based on discriminate and least squares criteria , 1979 .
[16] M. Oliviero,et al. Automatic differentiation of melanoma from melanocytic nevi with multispectral digital dermoscopy: a feasibility study. , 2001, Journal of the American Academy of Dermatology.
[17] S. R. Peterson,et al. Color Atlas of Dermatoscopy, 2nd ed , 2003 .
[18] F. Meyskens,et al. Cutaneous malignant melanoma (arizona cancer center experience). I. Natural history and prognostic factors influencing survival in patients with stage i disease , 1988, Cancer.
[19] P. Barbini,et al. Digital dermoscopy analysis and artificial neural network for the differentiation of clinically atypical pigmented skin lesions: a retrospective study. , 2002, The Journal of investigative dermatology.
[20] Wilhelm Stolz,et al. Color Atlas of Dermatoscopy , 1991 .
[21] C. Balch,et al. Tumor thickness as a guide to surgical management of clinical stage I melanoma patients , 1979, Cancer.
[22] Philippe Schmid-Saugeona,et al. Towards a computer-aided diagnosis system for pigmented skin lesions. , 2003, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.
[23] R. Hofmann-Wellenhof,et al. The dermoscopic classification of atypical melanocytic naevi (Clark naevi) is useful to discriminate benign from malignant melanocytic lesions , 2003, The British journal of dermatology.
[24] A. Green,et al. Computer image analysis in the diagnosis of melanoma. , 1994, Journal of the American Academy of Dermatology.