Semi-supervised change detection approach combining sparse fusion and constrained k means for multi-temporal remote sensing images

Change detection is the measure of the thematic change information that can guide to more tangible insights into an underlying process involving land cover, land usage and environmental changes. This paper deals with a semi-supervised change detection approach combining sparse fusion and constrained k means clustering on multi-temporal remote sensing images taken at different timings T1 and T2. Initially a remote sensing fusion method with sparse representation over learned dictionaries is applied to the difference images. The dictionaries are learned from the difference images adaptively. The fused image is calculated by combining the sparse coefficients and the dictionary. Finally the fused image is subjected to constrained k means (CKM) clustering combining few known labelled patterns and unlabelled patterns which have been collected from experts. The enhanced (CKM) approach (ECKM) is compared with k means, adaptive k means (AKM) and fuzzy c means (FCM). Experimental results were carried out on multi-temporal remote sensing images. Results obtained using PCC and F1 measure confirms the effectiveness of the proposed approach. It is also noticed that the ECKM provides better results with less misclassification of errors as compared to k means, adaptive k means and fuzzy c means

Multi-Level Fusion of CT and MRI Brain Images for Classifying Tumor

Abstract: Medical image processing is the most stimulating and developing field in our day today life. Now a day's processing of MRI images is one of the parts of this field This paper proposes an efficient method for detection of brain tumor from CT and MRI images of brain, by applying image fusion, segmentation, feature extraction and classification. Image Fusion is the process of combining relevant information from two or more images into a single composite image. First, the CT and MRI images of brain are subjected to multilevel fusion using discrete wavelet transform. The fusion strategy uses multi-level decomposition of the images obtained using wavelet transform. By analyzing the images at multiple levels, the method is able to extract finer details from them and in turn improves the quality of the fused image. The fused image is then segmented using morphological operations. And the features are extracted. Finally the extracted image is exposed to fuzzy based classification to identify whether the tumor is benign or malignant

Oral field cancerization and its clinical implications in the management in potentially malignant disorders

Oral cancer is one of the common malignancies reported in India. Most of these cancers are preceded by potentially malignant disorders. Despite improvements in the management strategies of these cancers the posttreatment prognosis has remained poor. The 5-year survival rates of oral cancers in most countries are still below 50%. The poor outcomes in oral cancer prevention and treatment can be due to nature of the spread of genetically altered cells as fields within the epithelial compartment. The conventional management protocols need to be modified taking into consideration the field spread of genetically altered cells

Cell immobilization technique for the enhanced removal of lindane using Streptomyces strains isolated from Northwestern Argentina

Lindane (γ-HCH) is an organochlorine insecticide which has a negative effect as a pollutant agent of soil, water and sediments. Nowadays it has been banned in almost all countries of the world, but its residues still remain in the environment. In this context, bioremediation, involving the use of microorganisms to degrade environmental contaminants, has received much attention as an effective biotechnological approach to clean up this kind of pollutants. Moreover, cell immobilization has been shown to present diverse advantages over conventional systems using free cells, such as the possibility of employing higher cell density, easier separation of cells from the system, repeated use of cells and better protection of cells from harsh environments. Thereby, this chapter compiles information about: 1) the advantages and limitations of the use of immobilized cells, 2) the comparison between free or immobilized cells for lindane removal by single cultures of actinobacteria, isolated from polluted environments in the northwest of Argentina, and 3) lindane removal by free and immobilized consortia of Streptomyces spp.Fil: Sáez, Juliana María. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Planta Piloto de Procesos Industriales Microbiológicos; ArgentinaFil: Benimeli, Claudia Susana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - CONICET - Tucumán. Unidad de Administración Territorial; Argentina. Universidad del Norte Santo Tomás de Aquino. Facultad de Ciencias de la Salud; ArgentinaFil: Amoroso, Maria Julia del R.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Planta Piloto de Procesos Industriales Microbiológicos; Argentina. Universidad Nacional de Tucumán. Facultad de Bioquímica, Química y Farmacia; Argentina. Universidad del Norte Santo Tomás de Aquino. Facultad de Ciencias de la Salud; Argentin