Automated epiluminescence microscopy: human vs machine in the diagnosis of melanoma.

O IL EPILUMINESCENCE microscopy (ELM), surface microscopy, dermatoscopy, and dermoscopy all refer to the same process of examination of cutaneous lesions with an incident light magnification system with oil at the skin-microscope interface. This technique greatly increases the morphological detail that is visualized, which results in an improvement in the diagnostic accuracy of most pigmented skin tumors, including melanoma. Well-defined ELM methods for the diagnosis of melanoma that are suitable for inexperienced clinicians have been developed, and detailed atlases are also available. This allows formal training in ELM that, not surprisingly, is necessary to improve diagnostic accuracy.

[1]  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.

[2]  W V Stoecker,et al.  Digital imaging in dermatology. , 1992, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[3]  C Bartoli,et al.  Results obtained by using a computerized image analysis system designed as an aid to diagnosis of cutaneous melanoma , 1992, Melanoma research.

[4]  K Wolff,et al.  Pigmented Spitz nevi: improvement of the diagnostic accuracy by epiluminescence microscopy. , 1992, Journal of the American Academy of Dermatology.

[5]  K Wolff,et al.  In vivo epiluminescence microscopy: improvement of early diagnosis of melanoma. , 1993, The Journal of investigative dermatology.

[6]  P Barbini,et al.  Digital dermoscopy analysis for the differentiation of atypical nevi and early melanoma: a new quantitative semiology. , 1999, Archives of dermatology.

[7]  A. Green,et al.  Computer image analysis in the diagnosis of melanoma. , 1994, Journal of the American Academy of Dermatology.

[8]  Wilhelm Stolz,et al.  Comparison of classification rates for conventional and dermatoscopic images of malignant and benign melanocytic lesions using computerized colour image analysis , 1993 .

[9]  Hugues Talbot,et al.  Automated Instrumentation for the Diagnosis of Invasive Melanoma: Image Analysis of Oil Epiluminescence Microscopy , 1997 .

[10]  S. Menzies An atlas of surface microscopy of pigmented skin lesions , 1996 .

[11]  R. Betti,et al.  Improvement of diagnostic accuracy in the clinical diagnosis of pigmented skin lesions by epiluminescence microscopy , 1996 .

[12]  P Bauer,et al.  Diagnosis of cutaneous melanoma: accuracy of a computerized image analysis system (Skin View) , 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.

[13]  Hugues Talbot,et al.  Automated instrumentation for the diagnosis of invasive melanoma: 042 , 1996 .

[14]  K Wolff,et al.  Epiluminescence microscopy of small pigmented skin lesions: short-term formal training improves the diagnostic performance of dermatologists. , 1997, Journal of the American Academy of Dermatology.

[15]  M. Binder,et al.  Epiluminescence microscopy. A useful tool for the diagnosis of pigmented skin lesions for formally trained dermatologists. , 1995, Archives of dermatology.

[16]  M A Weinstock,et al.  Basic skin cancer triage for teaching melanoma detection. , 1996, Journal of the American Academy of Dermatology.

[17]  G Pellacani,et al.  Digital videomicroscopy and image analysis with automatic classification for detection of thin melanomas. , 1999, Melanoma research.

[18]  S. Menzies,et al.  Frequency and morphologic characteristics of invasive melanomas lacking specific surface microscopic features. , 1996, Archives of dermatology.

[19]  G. Argenziano,et al.  Epiluminescence microscopy for the diagnosis of doubtful melanocytic skin lesions. Comparison of the ABCD rule of dermatoscopy and a new 7-point checklist based on pattern analysis. , 1998, Archives of dermatology.

[20]  T Burgdorf,et al.  The ABCD rule of dermatoscopy does not apply to small melanocytic skin lesions. , 2001, Archives of dermatology.

[21]  Robin Marks,et al.  Early detection of skin cancer , 1994, The Medical journal of Australia.

[22]  K Wolff,et al.  In vivo epiluminescence microscopy of pigmented skin lesions. II. Diagnosis of small pigmented skin lesions and early detection of malignant melanoma. , 1987, Journal of the American Academy of Dermatology.

[23]  E. Claridge,et al.  Computer screening for early detection of melanoma—is there a future? , 1995, The British journal of dermatology.

[24]  W. Dillon,et al.  Color Atlas of Dermatoscopy , 1996 .

[25]  G Pellacani,et al.  Digital videomicroscopy improves diagnostic accuracy for melanoma. , 1998, Journal of the American Academy of Dermatology.

[26]  K. Balanda,et al.  General practitioner and patient response during a public education program to encourage skin examinations , 1994, The Medical journal of Australia.

[27]  A. Sober,et al.  Computerized Digital Image Analysis: An Aid for Melanoma Diagnosis , 1994, The Journal of dermatology.

[28]  H. Kittler,et al.  Epiluminescence microscopy-based classification of pigmented skin lesions using computerized image analysis and an artificial neural network , 1998, Melanoma research.

[29]  R. H. Moss,et al.  Digital imaging in dermatology. , 1992, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[30]  C. Grin,et al.  Accuracy in the clinical diagnosis of malignant melanoma. , 1990, Archives of dermatology.