Texture description and segmentation through fractal geometry
Computer Vision, Graphics, and Image Processing
Reviewing State of the Art AI Systems for Skin Cancer Diagnosis
Proceedings of the 2007 conference on Emerging Artificial Intelligence Applications in Computer Engineering: Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies
Overview of advanced computer vision systems for skin lesions characterization
IEEE Transactions on Information Technology in Biomedicine - Special section on computational intelligence in medical systems
The lacunarity of colour fractal images
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Fractal dimension and lacunarity of psoriatic lesions: a colour approach
BEBI'09 Proceedings of the 2nd WSEAS international conference on Biomedical electronics and biomedical informatics
Towards video quality metrics based on colour fractal geometry
Journal on Image and Video Processing - Special issue on emerging methods for color image and video quality enhancement
Methodological review: Computerized analysis of pigmented skin lesions: A review
Artificial Intelligence in Medicine
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Melanocytic nevi are recognized as precursors of melanoma. Aiding in early recognition of melanoma, we estimated color texture parameters, fractal dimension and lacunarity of melanoma and other melanocytic nevi. Digital images of the lesions were processed. Graphic three-dimensional pseudoelevation images of the lesions and surrounding skin were produced to identify irregularities in color texture within the lesions. Estimation of lacunarity and fractal dimension followed in order to produce a numerical estimate of the coarseness of color texture. Clinicians readily perceive the resulting ''geographical'' images. Irregularity in the anaglyph, which might veil malignancy, is effortlessly identified through these images, and therefore an early excision of a suspect lesion is indicated.