Pigment distribution in melanocytic lesion images: a digital parameter to be employed for computer‐aided diagnosis

Background/purpose: Since in early melanoma (MM) and especially in in situ MM differential structures, which are diagnostic for MM may be lacking, pigment distribution asymmetry represents an important diagnostic feature. Our aim was to automatically assess pigment distribution in images referring to MMs, atypical nevi (AN) and clearly benign nevi (BN), and to evaluate the diagnostic capability of numerical parameters describing a non homogeneous distribution of pigmentation.

[1]  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.

[2]  J Smolle,et al.  Terminology in surface microscopy. Consensus meeting of the Committee on Analytical Morphology of the Arbeitsgemeinschaft Dermatologische Forschung, Hamburg, Federal Republic of Germany, Nov. 17, 1989. , 1990, Journal of the American Academy of Dermatology.

[3]  Wilhelm Stolz,et al.  Color Atlas of Dermatoscopy , 1991 .

[4]  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.

[5]  R. Kenet,et al.  Clinical diagnosis of pigmented lesions using digital epiluminescence microscopy. Grading protocol and atlas. , 1993, Archives of dermatology.

[6]  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.

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

[8]  S. Menzies,et al.  A sensitivity and specificity analysis of the surface microscopy features of invasive melanoma , 1996, Melanoma research.

[9]  W Stolz,et al.  Computer screening for early detection of melanoma ‐ is there a future? , 1996, The British journal of dermatology.

[10]  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.

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

[12]  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.

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

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

[15]  Giovanni Pellacani,et al.  Digital videomicroscopy with image analysis and automatic classification as an aid for diagnosis of Spitz nevus , 1999 .

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

[17]  H. Kittler,et al.  Follow-up of melanocytic skin lesions with digital epiluminescence microscopy: patterns of modifications observed in early melanoma, atypical nevi, and common nevi. , 2000, Journal of the American Academy of Dermatology.

[18]  S. Menzies,et al.  Short-term digital surface microscopic monitoring of atypical or changing melanocytic lesions. , 2001, Archives of dermatology.

[19]  R. Hofmann-Wellenhof,et al.  Dermoscopic classification of atypical melanocytic nevi (Clark nevi). , 2001, Archives of dermatology.

[20]  A. McMahon,et al.  The use of the dermatoscope to identify early melanoma using the three‐colour test , 2002, The British journal of dermatology.

[21]  E Epstein.  The use of the dermatoscope to identify early melanoma using the three‐colour test , 2002, The British journal of dermatology.

[22]  Harold S Rabinovitz,et al.  Pattern analysis: a two-step procedure for the dermoscopic diagnosis of melanoma. , 2002, Clinics in dermatology.

[23]  G Pellacani,et al.  Computer description of colours in dermoscopic melanocytic lesion images reproducing clinical assessment. , 2003, The British journal of dermatology.

[24]  M. G. Fleming,et al.  Dermoscopy of pigmented skin lesions: results of a consensus meeting via the Internet. , 2003, Journal of the American Academy of Dermatology.

[25]  Gernot Rassner,et al.  Modified ABC-point list of dermoscopy: A simplified and highly accurate dermoscopic algorithm for the diagnosis of cutaneous melanocytic lesions. , 2003, Journal of the American Academy of Dermatology.

[26]  Rita Cucchiara,et al.  A new algorithm for border description of polarized light surface microscopic images of pigmented skin lesions , 2003, IEEE Transactions on Medical Imaging.

[27]  Rita Cucchiara,et al.  Automated Extraction and Description of Dark Areas in Surface Microscopy Melanocytic Lesion Images , 2004, Dermatology.

[28]  Rita Cucchiara,et al.  Color calibration for a dermatological video camera system , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

[29]  G. Argenziano,et al.  Linear discriminant analysis of dermoscopic parameters for the differentiation of early melanomas from Clark naevi , 2004, Melanoma research.

[30]  Costantino Grana,et al.  Automated description of colours in polarized-light surface microscopy images of melanocytic lesions , 2004, Melanoma research.