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Breast cancer is a highly heterogeneous disease and very common among women worldwide. Inter-observer and intra-observer errors occur frequently in analyzing the lesion portion of medical images, giving high variability in results interpretations. Computer Aided Diagnosis system (CAD) plays a vital role to overcome this variability. Segmentation is the second critical stage in CAD system to extract...
DNA microarray technologies are leading to an explosion in available gene expression data which simultaneously monitor the expression pattern of thousands of genes. All the genes may not be biologically significant in diagnosing the disease. In this paper, a novel approach has been proposed to select significant genes of leukemia cancer using K-Means clustering algorithm. It is an unsupervised machine...
The objective of the paper is to analyze, assess and compare the flood area extent of multi polarization SAR images against the landuse/landcover units of disaster affected region. A comparative flood area assessment of L- and C-band SAR images of the same disaster region has been carried out. The output results which represent the deep, shallow and non-flooded regions of the input HH, HV and VV polarization...
Ultrasound imaging is a widely used technology for prostate cancer diagnosis and prognosis among the different medical image modalities. The ultrasound images are very difficult to segment because of poor image contrast, speckle noise, and missing or diffuse boundaries in the transrectal ultrasound (TRUS). So the significant application is the segmentation of the prostate in transrectal ultrasound...
This paper focuses on performance evaluation of the classification algorithms for problems of unbalanced and balanced large data sets. Three methods such as ELM, MRAN, and SRAN have been proposed for solving the set classification problem and studied. The ELM is based on randomly chosen hidden nodes and analytically determines the output weights of SLFNs. Then the next method M-RAN is a sequential...
This paper mainly highlights the technical challenges addressed while deploying an end user specific real time Geospatial collaborative system on the top of GARUDA Grid. The grid simulation results has been gathered in a automated mode from the computing clusters of the Grid and the results of equal time stamp have been merged by a centralized image processing unit which has been connected to a `Master...
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