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Lookup NU author(s): Khaled Marghani,
Professor Satnam Dlay,
Professor Bayan Sharif,
Dr Andrew SimsORCiD
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
In order to assist the decision of the pathologist in cancer diagnosis, a new algorithm using morphological analyses based on fractal geometry is investigated. Samples from two different colorectal tissue types were used, consisting of 24 microscopic images represent moderately differentiated adenocarcinoma, and 22 images of normal tissues. Morphological examinations based on boxcounting method were applied and fractal dimension (FD) were estimated. For validation, statistical analyses for assessing the identification of abnormalities (adenocarcinoma vs. normal mucosa) were performed. Obtained results show a very strong significance of 5.57013*10/sup -10/ using analysis of variance for comparing the means of two different populations of the independent FD observations. The potential for applying morphological analyses of histological microscopic images based on fractal features is established. In brief, quantitative measurements, based morphological features, provide useful information can help decision-making. Further research of combining advanced feature based morphology for pathological diagnosis is required. (21 References).
Author(s): Marghani K, Dlay S, Sharif B, Sims A
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: Communication Systems, Networks and Digital Signal Processing. CSNDSP 2004. Fourth International Symposium. Newcastle upon Tyne Univ. 2004
Year of Conference: 2004
Notes: Dlay SS
Newcastle upon Tyne, UK.
Communication Systems, Networks and Digital Signal Processing. CSNDSP 2004. Fourth International Symposium. Newcastle upon Tyne, UK. 20-22 July 2004.