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| Abstract: | The characterization and grading of glioma tumors, via image derived features, for diagnosis, prognosis, and treatment response has been an active research area in medical image computing. This paper presents a novel method for automatic detection and classification of glioma from conventional T2 weighted MR images. Automatic detection of the tumor was established using newly developed method called Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA).Statistical Features were extracted from the detected tumor texture using first order statistics and gray level co-occurrence matrix (GLCM) based second order statistical methods. Statistical significance of the features was determined by t-test and its corresponding p-value. A decision system was developed for the grade detection of glioma using these selected features and its p-value. The detection performance of the decision system was validated using the receiver operating characteristic (ROC) curve. The diagnosis and grading of glioma using this non-invasive method can contribute promising results in medical image computing |
| Description: | International Journal of Emerging Technologies in Computational and Applied Sciences, 7(1), December 2013- February, 2014, pp. 08-14 |
| URI: | http://dyuthi.cusat.ac.in/purl/4579 |
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| Automatic Detec ... g Statistical Features.pdf | (413.4Kb) |
| Abstract: | Southern Ocean (SO) is the fourth largest Ocean comprising the southern portions of the Atlantic Ocean, Indian Ocean and Pacific Ocean. Sediment core sample (660 34’S and 580 40’E)was collected onboard O.R.V Sagar Nidhi from January to March 2010 in the Fourth Southern Ocean expedition cruise launched by the National Centre for Antarctic and Ocean Research, Goa . Sedimentary records from this area reveal the sensitivity and climatic variability’s of the region over a large time scale. Organic matter (OM) and textural behaviour of the samples were analyzed and processed concurrently. Distribution of OM, Total Organic Carbon (TOC), Protein, Lipid and Carbohydrate along with the trace metal was highlighted. Textural variation was in the array of Sand >Clay >Silt. Sand content ranges from 30.29% to 80.11%. The order of relative distribution of OM was Lipid >Protein > TOC > Carbohydrate. The average concentrations of TOC, Protein, Lipid and Carbohydrate were 2.2 mg/g, 1.2 mg/g, 3.3 mg/g and 1.1mg/g respectively. Protein to carbohydrate ratio and lipid to carbohydrate ratio were also encountered to understand the respective freshness and nutritional quality of the sediments. Trace metal distribution showed the average concentration was maximum for Mn and minimum for Co. |
| Description: | Research Journal of Chemistry and Environment Vol.17(2) February (2013) |
| URI: | http://dyuthi.cusat.ac.in/purl/4616 |
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| Geochemistry of ... from antarctic region.pdf | (151.5Kb) |
| Abstract: | Distribution and chemistry of major inorganic forms of nutrients along with physico-chemical parameters were investigated. Surface sediments and overlying waters of the Ashtamudi and Vembanad Lakes were taken for the study, which is situated in the southwest coast of India. High concentrations of dissolved nitrogen and phosphorus compounds carried by the river leads to oxygen depletion in the water column. A concurrent increase in the bottom waters along with decrease in dissolved oxygen was noticed. This support to nitrification process operating in the sediment-water interface of the Ashtamudi and Vembanad Lake. Estuarine sediments are clayey sand to silty sand both in Ashtamudi and Vembanad in January and May. Present study indicates that the sediment texture is the major controlling factor in the distribution of these nutrient forms. For water samples nitrite, inorganic phosphate was high in Vembanad in January and May compared to Ashtamudi. For sediments, enhanced level of inorganic phosphate and nitrite was found in Vembanad during January and May. It had been observed that the level of N and P is more in sediments. A comparative assessment of the Ashtamudi and Vembanad Lake reveals that the Vembanad wetland is more deteriorated compared to the Ashtamudi wetland system |
| Description: | Indian Journal of Marine Sciences Vol. 38(4), December 2009, pp 451-456 |
| URI: | http://dyuthi.cusat.ac.in/purl/4615 |
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| Nutrient dynami ... lakes of Kerala, India.pdf | (1.039Mb) |
| Abstract: | Low grade and High grade Gliomas are tumors that originate in the glial cells. The main challenge in brain tumor diagnosis is whether a tumor is benign or malignant, primary or metastatic and low or high grade. Based on the patient's MRI, a radiologist could not differentiate whether it is a low grade Glioma or a high grade Glioma. Because both of these are almost visually similar, autopsy confirms the diagnosis of low grade with high-grade and infiltrative features. In this paper, textural description of Grade I and grade III Glioma are extracted using First order statistics and Gray Level Co-occurance Matrix Method (GLCM). Textural features are extracted from 16X16 sub image of the segmented Region of Interest(ROI) .In the proposed method, first order statistical features such as contrast, Intensity , Entropy, Kurtosis and spectral energy and GLCM features extracted were showed promising results. The ranges of these first order statistics and GLCM based features extracted are highly discriminant between grade I and Grade III. In this study which gives statistical textural information of grade I and grade III Glioma which is very useful for further classification and analysis and thus assisting Radiologist in greater extent. |
| Description: | Int. J. of Recent Trends in Engineering and Technology, Vol. 4, No. 3, Nov 2010 |
| URI: | http://dyuthi.cusat.ac.in/purl/4575 |
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| Texture Descrip ... features in Brain MRIs.pdf | (353.9Kb) |
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