Literature DB >> 25027713

[Fractal geometry in the objective grading of prostate carcinoma].

P Waliszewski1, F Wagenlehner, S Gattenlöhner, W Weidner.   

Abstract

BACKGROUND: A possible approach to objectively classify complex patterns in tumor tissue is a mathematical and statistical investigation of the distribution of cell nuclei as a geometric representation of cancer cells by fractal dimensions. Both the existence and changes in the fractal structure of tumor tissue have important consequences for the objective system of tumor grading. In addition, the complexity of growth in different carcinomas or their intercellular interactions can be compared to each other.
RESULTS: We present a theoretical introduction into fractal geometry as well as in the computer algorithms based upon the Rényi family of fractal dimensions. Finally, a geometric model of prostate cancer is introduced and the relationship between geometric patterns of prostate tumor and the fractal dimensions of the Rényi family are explained.

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Year:  2014        PMID: 25027713     DOI: 10.1007/s00120-014-3472-x

Source DB:  PubMed          Journal:  Urologe A        ISSN: 0340-2592            Impact factor:   0.639


  14 in total

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2.  Basic principles and applications of fractal geometry in pathology: a review.

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7.  Tissue as a self-organizing system with fractal dynamics.

Authors:  P Waliszewski; J Konarski
Journal:  Adv Space Res       Date:  2001       Impact factor: 2.152

8.  Fractals and cancer.

Authors:  J W Baish; R K Jain
Journal:  Cancer Res       Date:  2000-07-15       Impact factor: 12.701

9.  Fractal analysis of two-dimensional vascularity in primary prostate cancer and surrounding non-tumoral parenchyma.

Authors:  Gianluigi Taverna; Piergiuseppe Colombo; Fabio Grizzi; Barbara Franceschini; Giorgia Ceva-Grimaldi; Mauro Seveso; Guido Giusti; Alessandro Piccinelli; Pierpaolo Graziotti
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10.  Classifying prostate cancer malignancy by quantitative histomorphometry.

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  2 in total

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Review 2.  Artificial Intelligence in Lung Cancer Pathology Image Analysis.

Authors:  Shidan Wang; Donghan M Yang; Ruichen Rong; Xiaowei Zhan; Junya Fujimoto; Hongyu Liu; John Minna; Ignacio Ivan Wistuba; Yang Xie; Guanghua Xiao
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  2 in total

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