Search results for: Lamyaa%20Gamal%20El-Deen%20Taha
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3

Search results for: Lamyaa%20Gamal%20El-Deen%20Taha

3 Urban Land Cover from GF-2 Satellite Images Using Object Based and Neural Network Classifications

Authors: Lamyaa Gamal El-Deen Taha, Ashraf Sharawi

Abstract:

China launched satellite GF-2 in 2014. This study deals with comparing nearest neighbor object-based classification and neural network classification methods for classification of the fused GF-2 image. Firstly, rectification of GF-2 image was performed. Secondly, a comparison between nearest neighbor object-based classification and neural network classification for classification of fused GF-2 was performed. Thirdly, the overall accuracy of classification and kappa index were calculated. Results indicate that nearest neighbor object-based classification is better than neural network classification for urban mapping.

Keywords: GF-2 images, feature extraction-rectification, nearest neighbour object based classification, segmentation algorithms, neural network classification, multilayer perceptron

Procedia PDF Downloads 343
2 Assessment of Planet Image for Land Cover Mapping Using Soft and Hard Classifiers

Authors: Lamyaa Gamal El-Deen Taha, Ashraf Sharawi

Abstract:

Planet image is a new data source from planet lab. This research is concerned with the assessment of Planet image for land cover mapping. Two pixel based classifiers and one subpixel based classifier were compared. Firstly, rectification of Planet image was performed. Secondly, a comparison between minimum distance, maximum likelihood and neural network classifications for classification of Planet image was performed. Thirdly, the overall accuracy of classification and kappa coefficient were calculated. Results indicate that neural network classification is best followed by maximum likelihood classifier then minimum distance classification for land cover mapping.

Keywords: planet image, land cover mapping, rectification, neural network classification, multilayer perceptron, soft classifiers, hard classifiers

Procedia PDF Downloads 148
1 Indoleamine 2,3 Dioxygenase and Regulatory T Cells in Acute Myeloid Leukemia

Authors: Iman M. Mansour, Rania A. Zayed, Fadwa S. Abdel-Azim, Lamyaa H. Abdel-Latif

Abstract:

Background and Objectives: The microenvironment of acute myeloid leukemia (AML) is suppressive for immune cells. Regulatory T cells (Tregs) have been recognized to play a role in helping leukemic cells to evade immunesurveillance. The mesenchymal stem cells (MSCs) are essential contributors in immunomodulation of the microenvironment as they can promote differentiation of Tregs via the indoleamine 2,3-dioxygenase (IDO) pathway. The aim of the present work was to evaluate the expression of IDO in bone marrow derived MSCs and to study its correlation to percentage of Tregs. Methods: 37 adult bone marrow samples were cultured in appropriate culture medium to isolate MSCs. Successful harvest of MSCs was determined by plastic adherence, morphology and positive expression of CD271 and CD105; negative expression of CD34 and CD45 using flowcytometry. MSCs were examined for IDO expression by immunocytochemistry using anti-IDO monoclonal antibody. CD4+ CD25+ cells (Tregs) were measured in bone marrow samples by flowcytometry. Results: MSCs were successfully isolated from 20 of the 37 bone marrow samples cultured. MSCs showed higher expression of IDO and Tregs percentage was higher in AML patients compared to control subjects (p=0.002 and p<0.001 respectively). A positive correlation was found between IDO expression and Tregs percentage (p value=0.012, r=0.5). Conclusion: In this study, we revealed an association between high IDO expression in MSCs and elevated levels of Tregs which has an important role in the pathogenesis of AML, providing immunosuppressive microenvironment.

Keywords: acute myeloid leukemia, indoleamine 2, 3-dioxygenase, mesenchymal stem cells, T regulatory cells

Procedia PDF Downloads 324