Literature DB >> 8600802

Fractal and integer-dimensional geometric analysis of pigmented skin lesions.

S S Cross1, A J McDonagh, T J Stephenson, D W Cotton, J C Underwood.   

Abstract

Accurate in vivo diagnosis of pigmented skin lesions is required to identify and excise malignant melanomas but to avoid unnecessary excision of benign lesions; the published rates of clinical diagnostic accuracy are about 65%. This study investigates whether fractal geometric analysis of pigmented skin lesions can improve the rate of diagnostic accuracy. Forty-two pigmented skin lesions (15 malignant melanomas, 21 melanocytic naevi, and 6 basal cell papillomas) on patients attending a dermatology clinic were photographed, excised, and sent for histopathological examination. The fractal dimension of the boundary of the lesions was measured using a box-counting method implemented on a microcomputer-based image analysis system. Euclidean geometric parameters were also measured. The fractal dimension of all the lesions was greater than the topological dimension (one), indicating that there is a fractal element to their structure. Using all measured parameters together, multivariate linear discriminant analysis produced a confusion matrix in which 45% of the lesions were assigned to the correct diagnostic group with a kappa statistic of 0.33. There was no significant difference between the fractal dimension of melanocytic naevi and that of malignant melanomas (p = 0.18). Although pigmented skin lesions have a fractal element to their structure, the fractal dimension of their boundaries is not a useful morphometric discriminant between the diagnostic groups of malignant melanomas and benign melanocytic naevi.

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Mesh:

Year:  1995        PMID: 8600802     DOI: 10.1097/00000372-199508000-00012

Source DB:  PubMed          Journal:  Am J Dermatopathol        ISSN: 0193-1091            Impact factor:   1.533


  9 in total

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2.  Fractal characterisation of boundary irregularity in skin pigmented lesions.

Authors:  A Piantanelli; P Maponi; L Scalise; S Serresi; A Cialabrini; A Basso
Journal:  Med Biol Eng Comput       Date:  2005-07       Impact factor: 2.602

3.  Fractal Pennes and Cattaneo-Vernotte bioheat equations from product-like fractal geometry and their implications on cells in the presence of tumour growth.

Authors:  Rami Ahmad El-Nabulsi
Journal:  J R Soc Interface       Date:  2021-09-01       Impact factor: 4.293

4.  The universal dynamics of tumor growth.

Authors:  Antonio Brú; Sonia Albertos; José Luis Subiza; José López García-Asenjo; Isabel Brú
Journal:  Biophys J       Date:  2003-11       Impact factor: 4.033

Review 5.  Streamlining cutaneous melanomas in young women of the Belgian Mosan region.

Authors:  Trinh Hermanns-Lê; Sébastien Piérard
Journal:  Biomed Res Int       Date:  2014-02-25       Impact factor: 3.411

6.  A machine learning approach to automatic detection of irregularity in skin lesion border using dermoscopic images.

Authors:  Abder-Rahman Ali; Jingpeng Li; Guang Yang; Sally Jane O'Shea
Journal:  PeerJ Comput Sci       Date:  2020-06-29

7.  Fractal Dimension Analysis of Melanocytic Nevi and Melanomas in Normal and Polarized Light-A Preliminary Report.

Authors:  Paweł Popecki; Marcin Kozakiewicz; Marcin Ziętek; Kamil Jurczyszyn
Journal:  Life (Basel)       Date:  2022-07-07

8.  Wavelet-based 3D reconstruction of microcalcification clusters from two mammographic views: new evidence that fractal tumors are malignant and Euclidean tumors are benign.

Authors:  Kendra A Batchelder; Aaron B Tanenbaum; Seth Albert; Lyne Guimond; Pierre Kestener; Alain Arneodo; Andre Khalil
Journal:  PLoS One       Date:  2014-09-15       Impact factor: 3.240

9.  A Novel Fuzzy Multilayer Perceptron (F-MLP) for the Detection of Irregularity in Skin Lesion Border Using Dermoscopic Images.

Authors:  Abder-Rahman Ali; Jingpeng Li; Summrina Kanwal; Guang Yang; Amir Hussain; Sally Jane O'Shea
Journal:  Front Med (Lausanne)       Date:  2020-07-07
  9 in total

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