15 May 2003 Morphological and texture features for cancer tissues microscopic images
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Accurate and reliable decision making in cancer prognosis can help in the planning of appropriate surgery and therapy and, in general, optimize patient management through the different stages of the disease. In this paper, we present a novel fractal geometry algorithm as a potential method for classifying colorectal histopathological images. 102 microscopic samples of colon tissue were examined in order to identify abnormalities using a morphogical feature approach based on segmenting the image into different classes, derived from fractal dimension. The obtained mean fractal dimension (FD) for normal object tissue was 1.797+/- 0.0381 (n = 44) compared with 1.866+/-0.0262 for malignant samples (n = 58). In brief, this study was able to demonstrate the value of fractal dimension based on morphological approach in the analysis of microscopic colon cancer images. Although, the obtained results are strongly significant in the separation between normal and malignant colorectal images, further analyses are essential to incorporate this methodology into routine clinical practice by supporting pathologist decision.
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Khaled A. Marghani, Khaled A. Marghani, Satnam Singh Dlay, Satnam Singh Dlay, Bayan S. Sharif, Bayan S. Sharif, Andrew J. Sims, Andrew J. Sims, } "Morphological and texture features for cancer tissues microscopic images", Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); doi: 10.1117/12.481322; https://doi.org/10.1117/12.481322

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