A web-based application for dermoscopic measurements and learning

Image processing techniques have been long proposed for automatic analysis of skin lesions in the field of early detection of melanoma. Nevertheless, Computer Aided Systems are not yet able to outperform the diagnostic accuracy of expert dermatologists. They could instead reveal very useful in providing with a second opinion and improving the detection results from physicians with short clinical experience. The paper introduces an original web-based application for the automatic detection of dermoscopic structures within pigmented lesions and the support to novel dermatologists. It is able to receive and store digital images captured by digital cameras and smartphones equipped with dermoscopy, measure morphological and chromatic parameters, and take into account the measurement uncertainty to finally provide a clinical decision according to the diagnostic method 7-Point Checklist.

[1]  Gerald Schaefer,et al.  Lesion border detection in dermoscopy images , 2009, Comput. Medical Imaging Graph..

[2]  Begoña García Zapirain,et al.  Automated Detection of Melanoma in Dermoscopic Images , 2014 .

[3]  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.

[4]  J. Mayer,et al.  Systematic review of the diagnostic accuracy of dermatoscopy in detecting malignant melanoma , 1997, The Medical journal of Australia.

[5]  Catarina Barata,et al.  A System for the Detection of Pigment Network in Dermoscopy Images Using Directional Filters , 2012, IEEE Transactions on Biomedical Engineering.

[6]  T Lee,et al.  Dullrazor®: A software approach to hair removal from images , 1997, Comput. Biol. Medicine.

[7]  Bülent Sankur,et al.  Color image segmentation using histogram multithresholding and fusion , 2001, Image Vis. Comput..

[8]  Alfredo Paolillo,et al.  Automatic Diagnosis of Melanoma: A Software System Based on the 7-Point Check-List , 2010, 2010 43rd Hawaii International Conference on System Sciences.

[9]  G. Fabbrocini,et al.  Dermoscopic image-analysis system: estimation of atypical pigment network and atypical vascular pattern , 2006, IEEE International Workshop on Medical Measurement and Applications, 2006. MeMea 2006..

[10]  Wilhelm Burger,et al.  Digital Image Processing - An Algorithmic Introduction using Java , 2008, Texts in Computer Science.

[11]  Philippe Schmid.  Lesion detection in dermatoscopic images using anisotropic diffusion and morphological flooding , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[12]  M. Stella Atkins,et al.  A novel method for detection of pigment network in dermoscopic images using graphs , 2011, Comput. Medical Imaging Graph..

[13]  Masafumi Hagiwara,et al.  An improved Internet-based melanoma screening system with dermatologist-like tumor area extraction algorithm , 2008, Comput. Medical Imaging Graph..

[14]  A. Paolillo,et al.  A software tool for the diagnosis of melanomas , 2010, 2010 IEEE Instrumentation & Measurement Technology Conference Proceedings.

[15]  Alfredo Paolillo,et al.  Statistical Techniques Applied to the Automatic Diagnosis of Dermoscopic Images , 2012 .

[16]  David I. McLean,et al.  Generalizing Common Tasks in Automated Skin Lesion Diagnosis , 2011, IEEE Transactions on Information Technology in Biomedicine.