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Dariusz Lipiński and Wojciech Kacalak

microtopography characterization. Annals of the CIRP, 45, 589-598. [25] Lipiński, D., Kacalak, W., Tomkowski, R. (2014). Methodology of evaluation of abrasive tool wear with the use of laser scanning microscopy. Scanning, 36(1), 53-63, http://dx.doi.org/10.1002/sca.21088 [26] Beucher, S., Meyer, F. (1999). The morphological approach to segmentation: the watershed transformation. Dougherty, E.R (ed). Mathematical morphology in image processing. SPIE i IEEE Presses, Bellingham, WA, 433−481. [27] Wu, Q., Merchant, F.A., Castleman, K

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J. Mikulka, E. Gescheidtova and K. Bartusek

-scanning technique with supervised fuzzy pixel classification. Medical Image Analysis , 14, 13-20. Stawiaski, J., Decenciere, E., Bidault, F. (2008). Interactive liver tumor segmentation using graph-cuts and watershed. MiDAS Journal (MICCAI 2008 Workshop : Grand Challenge Liver Tumor Segmentation). http://www.insight-journal.org/browse/journal/45 http://www.insight-journal.org/browse/journal/45 Abdel-Massieh, N. H., Hadhoud, M. M., Amin, K. M. (2010). Automatic liver tumor segmentation from CT scans with knowledge

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Hezhong Yuan, Wei Pan, Zhengjie Zhu, Ying Wei, Qifang Geng and Shuqing An

Abstract

The concentrations of Zn, Cr, Cu, As, Cd, and Pb in sediment cores collected from a representative riverine wetland located in the Huaihe River watershed, China, dramaticlly increased from the bottom to upper layer of the cores. Application of principal component analysis (PCA) and enrichment factor (EF) suggested that heavy metals might primarily have been derived from the inflow of contaminated water from an industrial park and agricultural region. Component 1 of the PCA was dominated by Zn, Cr, Cu, Cd, and Pb, while Component 2 was dominated by As. Metals’ high concentrations and EF values showed that the anthropogenic pollutants have increased sharply in recent years and reflect the continuous development of industry and agriculture in the region of the wetland, with a corresponding dramatic deterioration of the environment due to constant effluent of pollutants. Cd exerted the highest potential ecological risk of individual metals of sediment cores. Additionally, integrated RI values for all metals indicated that sediments possessed low ecological risk from the bottom to about 6 cm depth of the cores, moderate ecological risk from about 5 cm depth upwards, then considerable ecological risk from 4 cm depth to the top layer of the sediment cores, which demonstrates a continuous deterioration of environmental quality in recent years in this region.

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Tomasz Bruździński, Adam Krzyżak, Thomas Fevens and Łukasz Jeleń

. Learning decision lists. Machine Learning , 2:229–246, 1987. [30] J.B.T.M Roerdink and A. Meijster. The watershed transform: definitions, algorithms, and parallelization strategies. Fundamenta Informaticae , 41:187–228, 2000. [31] W.N. Street, W.H. Wolberg, and O.L. Mangasarian. Nuclear feature extraction for breast tumor diagnosis. In IS&T/SPIE Inter. Symp. on Electronic Imaging: Science and Technology , volume 1905, pages 861–870, 1993. [32] W.H Wolberg and O.L. Mangasarian. Multisurface Method of Pattern Separation for Medical Diagnosis Applied to

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Sung-Duk Kim, Ho-Jin Lee and Byoung-Dong Oh

. (1994). Guide to Hydrological Practices, 5 th ed. Geneva: WMO. Korea Water Resources Corporation. (2004). Hydrological Report on Yongdam Watershed. K-water, 80-104.

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Z. Faizal Khan and A. Kannan

References [1] Armato, S.G., Giger, M.L., Moran, C.J. (1999). Computerized detection of pulmonary nodules on CT scans. Radio Graphics, 19, 1303-1311. [2] Hu, S., Huffman, E.A., Reinhardt, J.M. (2001). Automatic lung segmentation for accurate quantification of volumetric X-Ray CT images. IEEE Transactions on Medical Imging, 20 (6), 490-498. [3] Grau, V., Mewes, A.U., Alcaniz, M., Kikinis, R., Warfield, S.K. (2004). Improved watershed transform for medical image segmentation using prior information. IEEE

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T. Y. Wu and S. F. Lin

).Interactive liver tumor segmentation using graph-cuts and watershed. In Workshop on 3D Segmentation in the Clinic: A Grand Challenge II. Liver Tumor Segmentation Challenge (MICCAI 2008). [4] Seo, K.S., Chung, T.W. (2005). Automatic boundary tumor segmentation of a liver. In Computational Science and Its Applications (ICCSA 2005) , LNCS3483. Springer, 836-842. [5] Hadjiiski, L., Sahiner, B., Chan, H.P., Petrick, N., Helvie, M.A., Gurcan, M. (2001). Analysis of temporal changes of mammographic features: Computer-aided classification of

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Jiajun He, Huimin Zhang, Hui Zhang, Xuan Guo, Mingwei Song, Junhao Zhang and Xiaotao Li

Abstract

The distribution and extent of heavy metal accumulation in the fluvial sediment of the Beijiang River are described. The potential toxicity of this pollution was quantified using a consensus based sediment quality guidelines (SQGs) method and the Hakanson potential ecological risk index. The concentrations of Hg, As, Cu, Zn, Pb, Ni and Cr were high enough to damage the sediment biota on a frequent basis. The potential ecological risk was much higher in the downstream, urbanized reaches of the river than in the upstream reaches which are still rural, but all sections of the river posed at least a moderate level of ecological risk. Estimates of the economic loss associated with these pollutions were appreciable, and were mainly due to Hg and Cu. The Beijiang River basin is heavily polluted, posing environmental risks for the downstream reaches of the Pearl River, and economic loss to the whole watershed.

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Agnieszka Stec and Daniel Słyś

Water Res Associat 2002;38(3):835-845. [5] Burton GA, Pitt RE. Stormwater Effects Handbook: A Toolbox for Watershed Managers Scientists, and Engineers. CRC Press, 2002, Florida. http://www.epa.gov/ednnrmrl/publish/book/handbook/index.htm [6] Konrad CP, Booth DB. Hydrologic Trends Associated with Urban Development for Selected Streams in the Puget Sound Basin, Western Washington. U. S. Geological Survey Water Resources Investigations Report 02-4040. U.S. Geological Survey, U.S. Department of the Interior, 2002. Tacoma, Washington. http

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Sebastian Dudzik

Polish) Nieniewski M. (2005). Segmentation of Digital images. Watershed segmentation methods. Warsaw: Academic Publishing Office EXIT. (in Polish)